1919 lines
582 KiB
Plaintext
1919 lines
582 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"#! pip install tensorflow\n",
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"#! pip install scikit-learn\n",
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"train = pd.read_csv(\"train.csv\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"0 poznan.wuoz.gov.pl\n",
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"1 vill.okawa.kochi.jp\n",
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"2 nationalfinance.co.om\n",
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"3 town.ozora.hokkaido.jp\n",
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"4 open24.ie-news.irish/online/Login\n",
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" ... \n",
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"6995051 ddht.co.kr\n",
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"6995052 www.upstartepoxy.com\n",
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"6995053 employeesalaryschedule70.000webhostapp.com/adb...\n",
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"6995054 dekalbtool.com\n",
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"6995055 helpinganimals.com\n",
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"Name: URL_clean, Length: 6995056, dtype: object"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# 대괄호 [ ] 제거\n",
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"train['URL_clean'] = train['URL'].str.replace(r'[\\[\\]]', '', regex=True)\n",
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"train[\"URL_clean\"]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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||
"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
|
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>ID</th>\n",
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" <th>URL</th>\n",
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" <th>label</th>\n",
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" <th>URL_clean</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>TRAIN_0000000</td>\n",
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" <td>poznan[.]wuoz[.]gov[.]pl</td>\n",
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" <td>0</td>\n",
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" <td>poznan.wuoz.gov.pl</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>TRAIN_0000001</td>\n",
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" <td>vill[.]okawa[.]kochi[.]jp</td>\n",
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" <td>0</td>\n",
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" <td>vill.okawa.kochi.jp</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>TRAIN_0000002</td>\n",
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" <td>nationalfinance[.]co[.]om</td>\n",
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" <td>0</td>\n",
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" <td>nationalfinance.co.om</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>TRAIN_0000003</td>\n",
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" <td>town[.]ozora[.]hokkaido[.]jp</td>\n",
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" <td>0</td>\n",
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" <td>town.ozora.hokkaido.jp</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>TRAIN_0000004</td>\n",
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" <td>open24[.]ie-news[.]irish/online/Login</td>\n",
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" <td>1</td>\n",
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" <td>open24.ie-news.irish/online/Login</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6995051</th>\n",
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" <td>TRAIN_6995051</td>\n",
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" <td>ddht[.]co[.]kr</td>\n",
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" <td>0</td>\n",
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" <td>ddht.co.kr</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6995052</th>\n",
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" <td>TRAIN_6995052</td>\n",
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" <td>www[.]upstartepoxy[.]com</td>\n",
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" <td>0</td>\n",
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" <td>www.upstartepoxy.com</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6995053</th>\n",
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" <td>TRAIN_6995053</td>\n",
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" <td>employeesalaryschedule70[.]000webhostapp[.]com...</td>\n",
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" <td>1</td>\n",
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" <td>employeesalaryschedule70.000webhostapp.com/adb...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6995054</th>\n",
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" <td>TRAIN_6995054</td>\n",
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" <td>dekalbtool[.]com</td>\n",
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" <td>0</td>\n",
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" <td>dekalbtool.com</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6995055</th>\n",
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" <td>TRAIN_6995055</td>\n",
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" <td>helpinganimals[.]com</td>\n",
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" <td>0</td>\n",
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" <td>helpinganimals.com</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>6995056 rows × 4 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" ID URL \\\n",
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"0 TRAIN_0000000 poznan[.]wuoz[.]gov[.]pl \n",
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"1 TRAIN_0000001 vill[.]okawa[.]kochi[.]jp \n",
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"2 TRAIN_0000002 nationalfinance[.]co[.]om \n",
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"3 TRAIN_0000003 town[.]ozora[.]hokkaido[.]jp \n",
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"4 TRAIN_0000004 open24[.]ie-news[.]irish/online/Login \n",
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"... ... ... \n",
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"6995051 TRAIN_6995051 ddht[.]co[.]kr \n",
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"6995052 TRAIN_6995052 www[.]upstartepoxy[.]com \n",
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"6995053 TRAIN_6995053 employeesalaryschedule70[.]000webhostapp[.]com... \n",
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"6995054 TRAIN_6995054 dekalbtool[.]com \n",
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"6995055 TRAIN_6995055 helpinganimals[.]com \n",
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"\n",
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" label URL_clean \n",
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"0 0 poznan.wuoz.gov.pl \n",
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"1 0 vill.okawa.kochi.jp \n",
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"2 0 nationalfinance.co.om \n",
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"3 0 town.ozora.hokkaido.jp \n",
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"4 1 open24.ie-news.irish/online/Login \n",
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"... ... ... \n",
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"6995051 0 ddht.co.kr \n",
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"6995052 0 www.upstartepoxy.com \n",
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"6995053 1 employeesalaryschedule70.000webhostapp.com/adb... \n",
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"6995054 0 dekalbtool.com \n",
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"6995055 0 helpinganimals.com \n",
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"\n",
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"[6995056 rows x 4 columns]"
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]
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},
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||
"execution_count": 7,
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||
"metadata": {},
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||
"output_type": "execute_result"
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||
}
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],
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"source": [
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"train"
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||
]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"# url 엔트로피 차수 저장 \n",
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"import math\n",
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"\n",
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"def calculate_entropy(url):\n",
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" probability = [url.count(c) / len(url) for c in set(url)]\n",
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" return -sum(p * math.log(p, 2) for p in probability)\n"
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]
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},
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{
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||
"cell_type": "code",
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||
"execution_count": 9,
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||
"metadata": {},
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||
"outputs": [],
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||
"source": [
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||
"import re\n",
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"\n",
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"train['dot_count'] = train['URL_clean'].str.count(r'\\.')\n",
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"train['digit_count'] = train['URL_clean'].str.count(r'\\d')\n",
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"train['alpha_count'] = train['URL_clean'].str.count(r'[a-zA-Z]')\n",
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||
"train['dash_count'] = train['URL_clean'].str.count(r'-')\n",
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||
"train['underscore_count'] = train['URL_clean'].str.count(r'_')\n",
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"train['digit_count'] = train['URL_clean'].str.count(r'\\d')\n",
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"train['percent_count'] = train['URL_clean'].str.count(r'%')\n",
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"train['equal_count'] = train['URL_clean'].str.count(r'=')\n",
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"train['question_count'] = train['URL_clean'].str.count(r'\\?')\n",
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||
"train['at_count'] = train['URL_clean'].str.count(r'@')\n",
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"train['subdomain_count'] = train['URL_clean'].str.count(r'\\.')\n",
|
||
"train['length_of_url'] = train['URL_clean'].str.len()\n",
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||
"train['path_length'] = train['URL_clean'].str.extract(r'https?://[^/]+(/.*)')[0].str.len()\n",
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||
"train['top_level_domain_count'] = train['URL_clean'].str.count(r'\\.[a-zA-Z]{2,}')\n",
|
||
"train['is_ip_in_url'] = train['URL_clean'].apply(lambda x: bool(re.search(r'\\b(?:\\d{1,3}\\.){3}\\d{1,3}\\b', x)))\n",
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||
"train['special_char_count'] = train['URL_clean'].str.count(r'[^a-zA-Z0-9]')\n",
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||
"train['count_of_double_slash'] = train['URL_clean'].str.count(r'//')\n",
|
||
"train['subdomain_to_domain_ratio'] = train['subdomain_count'] / (train['dot_count'] + 1)\n",
|
||
"train['url_entropy'] = train['URL_clean'].apply(calculate_entropy)\n",
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||
"# www 포함 여부\n",
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||
"train['has_www'] = train['URL_clean'].str.contains('www')\n",
|
||
"# suspicious word 포함 여부\n",
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||
"suspicious_words = ['login', 'verify', 'update', 'confirm', 'account', 'secure', 'ebayisapi', 'banking']\n",
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||
"train['suspicious_word_count'] = train['URL_clean'].apply(lambda x: sum(word in x.lower() for word in suspicious_words))\n",
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||
"# 숫자 비율 (전체 길이 대비)\n",
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"train['digit_ratio'] = train['digit_count'] / (train['length_of_url'] + 1)\n",
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"# 알파벳 비율\n",
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"train['alpha_ratio'] = train['alpha_count'] / (train['length_of_url'] + 1)\n",
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"# 특수문자 비율\n",
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"train['special_ratio'] = train['special_char_count'] / (train['length_of_url'] + 1)\n",
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"# path 깊이 (슬래시 개수 기반)\n",
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"train['path_depth'] = train['URL_clean'].str.count(r'/') - 2 # 도메인 뒤의 / 개수 (http:// 제외)\n",
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"# 도메인 길이 (host만 추출해서)\n",
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"train['domain_length'] = train['URL_clean'].str.extract(r'https?://([^/]+)')[0].str.len()\n",
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||
"# 숫자 연속 등장 (ex: 1234 같은 경우)\n",
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"train['has_long_digit_sequence'] = train['URL_clean'].str.contains(r'\\d{4,}')\n",
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"# 하이픈 연속 등장 여부\n",
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||
"train['has_multiple_dash'] = train['URL_clean'].str.contains(r'-{2,}')\n"
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||
]
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||
},
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||
{
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"cell_type": "code",
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"execution_count": 10,
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||
"metadata": {},
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||
"outputs": [
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||
{
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"data": {
|
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"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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||
" }\n",
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||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
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" vertical-align: top;\n",
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||
" }\n",
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||
"\n",
|
||
" .dataframe thead th {\n",
|
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" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>ID</th>\n",
|
||
" <th>URL</th>\n",
|
||
" <th>label</th>\n",
|
||
" <th>URL_clean</th>\n",
|
||
" <th>dot_count</th>\n",
|
||
" <th>digit_count</th>\n",
|
||
" <th>alpha_count</th>\n",
|
||
" <th>dash_count</th>\n",
|
||
" <th>underscore_count</th>\n",
|
||
" <th>percent_count</th>\n",
|
||
" <th>...</th>\n",
|
||
" <th>url_entropy</th>\n",
|
||
" <th>has_www</th>\n",
|
||
" <th>suspicious_word_count</th>\n",
|
||
" <th>digit_ratio</th>\n",
|
||
" <th>alpha_ratio</th>\n",
|
||
" <th>special_ratio</th>\n",
|
||
" <th>path_depth</th>\n",
|
||
" <th>domain_length</th>\n",
|
||
" <th>has_long_digit_sequence</th>\n",
|
||
" <th>has_multiple_dash</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>TRAIN_0000000</td>\n",
|
||
" <td>poznan[.]wuoz[.]gov[.]pl</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>poznan.wuoz.gov.pl</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>15</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>3.308271</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.789474</td>\n",
|
||
" <td>0.157895</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>TRAIN_0000001</td>\n",
|
||
" <td>vill[.]okawa[.]kochi[.]jp</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>vill.okawa.kochi.jp</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>16</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>3.471354</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.800000</td>\n",
|
||
" <td>0.150000</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>TRAIN_0000002</td>\n",
|
||
" <td>nationalfinance[.]co[.]om</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>nationalfinance.co.om</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>19</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>3.272804</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.863636</td>\n",
|
||
" <td>0.090909</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>TRAIN_0000003</td>\n",
|
||
" <td>town[.]ozora[.]hokkaido[.]jp</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>town.ozora.hokkaido.jp</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>19</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>3.533771</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.826087</td>\n",
|
||
" <td>0.130435</td>\n",
|
||
" <td>-2</td>\n",
|
||
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|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>TRAIN_0000004</td>\n",
|
||
" <td>open24[.]ie-news[.]irish/online/Login</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>open24.ie-news.irish/online/Login</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>26</td>\n",
|
||
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|
||
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||
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|
||
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||
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||
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|
||
" <td>1</td>\n",
|
||
" <td>0.058824</td>\n",
|
||
" <td>0.764706</td>\n",
|
||
" <td>0.147059</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
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|
||
" <tr>\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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|
||
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|
||
" <td>...</td>\n",
|
||
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|
||
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|
||
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|
||
" <td>TRAIN_6995051</td>\n",
|
||
" <td>ddht[.]co[.]kr</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>ddht.co.kr</td>\n",
|
||
" <td>2</td>\n",
|
||
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|
||
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||
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||
" <td>0</td>\n",
|
||
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|
||
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|
||
" <td>2.921928</td>\n",
|
||
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|
||
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|
||
" <td>0.000000</td>\n",
|
||
" <td>0.727273</td>\n",
|
||
" <td>0.181818</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6995052</th>\n",
|
||
" <td>TRAIN_6995052</td>\n",
|
||
" <td>www[.]upstartepoxy[.]com</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>www.upstartepoxy.com</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>18</td>\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" <td>True</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.857143</td>\n",
|
||
" <td>0.095238</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6995053</th>\n",
|
||
" <td>TRAIN_6995053</td>\n",
|
||
" <td>employeesalaryschedule70[.]000webhostapp[.]com...</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>employeesalaryschedule70.000webhostapp.com/adb...</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>5</td>\n",
|
||
" <td>41</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>4.130881</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.098039</td>\n",
|
||
" <td>0.803922</td>\n",
|
||
" <td>0.078431</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6995054</th>\n",
|
||
" <td>TRAIN_6995054</td>\n",
|
||
" <td>dekalbtool[.]com</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>dekalbtool.com</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>13</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
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|
||
" <td>3.324863</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.866667</td>\n",
|
||
" <td>0.066667</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6995055</th>\n",
|
||
" <td>TRAIN_6995055</td>\n",
|
||
" <td>helpinganimals[.]com</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>helpinganimals.com</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>17</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>3.614369</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.894737</td>\n",
|
||
" <td>0.052632</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>6995056 rows × 31 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" ID URL \\\n",
|
||
"0 TRAIN_0000000 poznan[.]wuoz[.]gov[.]pl \n",
|
||
"1 TRAIN_0000001 vill[.]okawa[.]kochi[.]jp \n",
|
||
"2 TRAIN_0000002 nationalfinance[.]co[.]om \n",
|
||
"3 TRAIN_0000003 town[.]ozora[.]hokkaido[.]jp \n",
|
||
"4 TRAIN_0000004 open24[.]ie-news[.]irish/online/Login \n",
|
||
"... ... ... \n",
|
||
"6995051 TRAIN_6995051 ddht[.]co[.]kr \n",
|
||
"6995052 TRAIN_6995052 www[.]upstartepoxy[.]com \n",
|
||
"6995053 TRAIN_6995053 employeesalaryschedule70[.]000webhostapp[.]com... \n",
|
||
"6995054 TRAIN_6995054 dekalbtool[.]com \n",
|
||
"6995055 TRAIN_6995055 helpinganimals[.]com \n",
|
||
"\n",
|
||
" label URL_clean dot_count \\\n",
|
||
"0 0 poznan.wuoz.gov.pl 3 \n",
|
||
"1 0 vill.okawa.kochi.jp 3 \n",
|
||
"2 0 nationalfinance.co.om 2 \n",
|
||
"3 0 town.ozora.hokkaido.jp 3 \n",
|
||
"4 1 open24.ie-news.irish/online/Login 2 \n",
|
||
"... ... ... ... \n",
|
||
"6995051 0 ddht.co.kr 2 \n",
|
||
"6995052 0 www.upstartepoxy.com 2 \n",
|
||
"6995053 1 employeesalaryschedule70.000webhostapp.com/adb... 2 \n",
|
||
"6995054 0 dekalbtool.com 1 \n",
|
||
"6995055 0 helpinganimals.com 1 \n",
|
||
"\n",
|
||
" digit_count alpha_count dash_count underscore_count \\\n",
|
||
"0 0 15 0 0 \n",
|
||
"1 0 16 0 0 \n",
|
||
"2 0 19 0 0 \n",
|
||
"3 0 19 0 0 \n",
|
||
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|
||
"... ... ... ... ... \n",
|
||
"6995051 0 8 0 0 \n",
|
||
"6995052 0 18 0 0 \n",
|
||
"6995053 5 41 0 0 \n",
|
||
"6995054 0 13 0 0 \n",
|
||
"6995055 0 17 0 0 \n",
|
||
"\n",
|
||
" percent_count ... url_entropy has_www suspicious_word_count \\\n",
|
||
"0 0 ... 3.308271 False 0 \n",
|
||
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|
||
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|
||
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|
||
"4 0 ... 3.772450 False 1 \n",
|
||
"... ... ... ... ... ... \n",
|
||
"6995051 0 ... 2.921928 False 0 \n",
|
||
"6995052 0 ... 3.684184 True 0 \n",
|
||
"6995053 0 ... 4.130881 False 0 \n",
|
||
"6995054 0 ... 3.324863 False 0 \n",
|
||
"6995055 0 ... 3.614369 False 0 \n",
|
||
"\n",
|
||
" digit_ratio alpha_ratio special_ratio path_depth domain_length \\\n",
|
||
"0 0.000000 0.789474 0.157895 -2 NaN \n",
|
||
"1 0.000000 0.800000 0.150000 -2 NaN \n",
|
||
"2 0.000000 0.863636 0.090909 -2 NaN \n",
|
||
"3 0.000000 0.826087 0.130435 -2 NaN \n",
|
||
"4 0.058824 0.764706 0.147059 0 NaN \n",
|
||
"... ... ... ... ... ... \n",
|
||
"6995051 0.000000 0.727273 0.181818 -2 NaN \n",
|
||
"6995052 0.000000 0.857143 0.095238 -2 NaN \n",
|
||
"6995053 0.098039 0.803922 0.078431 0 NaN \n",
|
||
"6995054 0.000000 0.866667 0.066667 -2 NaN \n",
|
||
"6995055 0.000000 0.894737 0.052632 -2 NaN \n",
|
||
"\n",
|
||
" has_long_digit_sequence has_multiple_dash \n",
|
||
"0 False False \n",
|
||
"1 False False \n",
|
||
"2 False False \n",
|
||
"3 False False \n",
|
||
"4 False False \n",
|
||
"... ... ... \n",
|
||
"6995051 False False \n",
|
||
"6995052 False False \n",
|
||
"6995053 False False \n",
|
||
"6995054 False False \n",
|
||
"6995055 False False \n",
|
||
"\n",
|
||
"[6995056 rows x 31 columns]"
|
||
]
|
||
},
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
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|
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|
||
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|
||
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|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"features = [col for col in train.columns if col not in ['URL_clean']]\n",
|
||
"X = train[features]\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
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|
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" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>TRAIN_0000004</td>\n",
|
||
" <td>open24[.]ie-news[.]irish/online/Login</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>26</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>3.772450</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>0.058824</td>\n",
|
||
" <td>0.764706</td>\n",
|
||
" <td>0.147059</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>...</th>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6995051</th>\n",
|
||
" <td>TRAIN_6995051</td>\n",
|
||
" <td>ddht[.]co[.]kr</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>8</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>2.921928</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.727273</td>\n",
|
||
" <td>0.181818</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6995052</th>\n",
|
||
" <td>TRAIN_6995052</td>\n",
|
||
" <td>www[.]upstartepoxy[.]com</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>18</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>3.684184</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.857143</td>\n",
|
||
" <td>0.095238</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6995053</th>\n",
|
||
" <td>TRAIN_6995053</td>\n",
|
||
" <td>employeesalaryschedule70[.]000webhostapp[.]com...</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>5</td>\n",
|
||
" <td>41</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>4.130881</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.098039</td>\n",
|
||
" <td>0.803922</td>\n",
|
||
" <td>0.078431</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6995054</th>\n",
|
||
" <td>TRAIN_6995054</td>\n",
|
||
" <td>dekalbtool[.]com</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>13</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>3.324863</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.866667</td>\n",
|
||
" <td>0.066667</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6995055</th>\n",
|
||
" <td>TRAIN_6995055</td>\n",
|
||
" <td>helpinganimals[.]com</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>17</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>3.614369</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.894737</td>\n",
|
||
" <td>0.052632</td>\n",
|
||
" <td>-2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>6995056 rows × 30 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" ID URL \\\n",
|
||
"0 TRAIN_0000000 poznan[.]wuoz[.]gov[.]pl \n",
|
||
"1 TRAIN_0000001 vill[.]okawa[.]kochi[.]jp \n",
|
||
"2 TRAIN_0000002 nationalfinance[.]co[.]om \n",
|
||
"3 TRAIN_0000003 town[.]ozora[.]hokkaido[.]jp \n",
|
||
"4 TRAIN_0000004 open24[.]ie-news[.]irish/online/Login \n",
|
||
"... ... ... \n",
|
||
"6995051 TRAIN_6995051 ddht[.]co[.]kr \n",
|
||
"6995052 TRAIN_6995052 www[.]upstartepoxy[.]com \n",
|
||
"6995053 TRAIN_6995053 employeesalaryschedule70[.]000webhostapp[.]com... \n",
|
||
"6995054 TRAIN_6995054 dekalbtool[.]com \n",
|
||
"6995055 TRAIN_6995055 helpinganimals[.]com \n",
|
||
"\n",
|
||
" label dot_count digit_count alpha_count dash_count \\\n",
|
||
"0 0 3 0 15 0 \n",
|
||
"1 0 3 0 16 0 \n",
|
||
"2 0 2 0 19 0 \n",
|
||
"3 0 3 0 19 0 \n",
|
||
"4 1 2 2 26 1 \n",
|
||
"... ... ... ... ... ... \n",
|
||
"6995051 0 2 0 8 0 \n",
|
||
"6995052 0 2 0 18 0 \n",
|
||
"6995053 1 2 5 41 0 \n",
|
||
"6995054 0 1 0 13 0 \n",
|
||
"6995055 0 1 0 17 0 \n",
|
||
"\n",
|
||
" underscore_count percent_count equal_count ... url_entropy \\\n",
|
||
"0 0 0 0 ... 3.308271 \n",
|
||
"1 0 0 0 ... 3.471354 \n",
|
||
"2 0 0 0 ... 3.272804 \n",
|
||
"3 0 0 0 ... 3.533771 \n",
|
||
"4 0 0 0 ... 3.772450 \n",
|
||
"... ... ... ... ... ... \n",
|
||
"6995051 0 0 0 ... 2.921928 \n",
|
||
"6995052 0 0 0 ... 3.684184 \n",
|
||
"6995053 0 0 0 ... 4.130881 \n",
|
||
"6995054 0 0 0 ... 3.324863 \n",
|
||
"6995055 0 0 0 ... 3.614369 \n",
|
||
"\n",
|
||
" has_www suspicious_word_count digit_ratio alpha_ratio \\\n",
|
||
"0 False 0 0.000000 0.789474 \n",
|
||
"1 False 0 0.000000 0.800000 \n",
|
||
"2 False 0 0.000000 0.863636 \n",
|
||
"3 False 0 0.000000 0.826087 \n",
|
||
"4 False 1 0.058824 0.764706 \n",
|
||
"... ... ... ... ... \n",
|
||
"6995051 False 0 0.000000 0.727273 \n",
|
||
"6995052 True 0 0.000000 0.857143 \n",
|
||
"6995053 False 0 0.098039 0.803922 \n",
|
||
"6995054 False 0 0.000000 0.866667 \n",
|
||
"6995055 False 0 0.000000 0.894737 \n",
|
||
"\n",
|
||
" special_ratio path_depth domain_length has_long_digit_sequence \\\n",
|
||
"0 0.157895 -2 NaN False \n",
|
||
"1 0.150000 -2 NaN False \n",
|
||
"2 0.090909 -2 NaN False \n",
|
||
"3 0.130435 -2 NaN False \n",
|
||
"4 0.147059 0 NaN False \n",
|
||
"... ... ... ... ... \n",
|
||
"6995051 0.181818 -2 NaN False \n",
|
||
"6995052 0.095238 -2 NaN False \n",
|
||
"6995053 0.078431 0 NaN False \n",
|
||
"6995054 0.066667 -2 NaN False \n",
|
||
"6995055 0.052632 -2 NaN False \n",
|
||
"\n",
|
||
" has_multiple_dash \n",
|
||
"0 False \n",
|
||
"1 False \n",
|
||
"2 False \n",
|
||
"3 False \n",
|
||
"4 False \n",
|
||
"... ... \n",
|
||
"6995051 False \n",
|
||
"6995052 False \n",
|
||
"6995053 False \n",
|
||
"6995054 False \n",
|
||
"6995055 False \n",
|
||
"\n",
|
||
"[6995056 rows x 30 columns]"
|
||
]
|
||
},
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"X\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"y = train['label']\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ID object\n",
|
||
"URL object\n",
|
||
"URL_clean object\n",
|
||
"path_length object\n",
|
||
"domain_length object\n",
|
||
"dtype: object\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(train.dtypes[train.dtypes == 'object']) # 문자열 컬럼 확인"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# bool 컬럼들을 int로 변환\n",
|
||
"bool_cols = [\n",
|
||
" 'has_www', 'is_ip_in_url',\n",
|
||
" 'has_long_digit_sequence', 'has_multiple_dash'\n",
|
||
"]\n",
|
||
"\n",
|
||
"for col in bool_cols:\n",
|
||
" if col in train.columns:\n",
|
||
" train[col] = train[col].astype(int)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"상관계수 0.9 이상 피처 제거 목록: {'subdomain_count', 'top_level_domain_count', 'length_of_url'}\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 1500x1200 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"import seaborn as sns\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"# 1. 숫자형 피처만 추출 (label, has_https는 제외)\n",
|
||
"base_features = [col for col in train.columns \n",
|
||
" if train[col].dtype in ['int64', 'float64'] \n",
|
||
" and col not in ['label', 'has_https']]\n",
|
||
"\n",
|
||
"# 2. 상관계수 행렬 계산\n",
|
||
"corr_matrix = train[base_features].corr()\n",
|
||
"\n",
|
||
"# 3. 상관계수 0.9 이상인 피처 중 하나씩 제거할 리스트 만들기\n",
|
||
"to_drop = set()\n",
|
||
"for i in range(len(corr_matrix.columns)):\n",
|
||
" for j in range(i):\n",
|
||
" if abs(corr_matrix.iloc[i, j]) > 0.9:\n",
|
||
" colname_i = corr_matrix.columns[i]\n",
|
||
" colname_j = corr_matrix.columns[j]\n",
|
||
" # 둘 중 하나만 제거 (여기선 i번째를 제거)\n",
|
||
" to_drop.add(colname_i)\n",
|
||
"\n",
|
||
"print(\"상관계수 0.9 이상 피처 제거 목록:\", to_drop)\n",
|
||
"\n",
|
||
"# 4. 최종 features 리스트 생성\n",
|
||
"features = [col for col in base_features if col not in to_drop]\n",
|
||
"\n",
|
||
"# 5. 히트맵 그리기용 상관계수 행렬\n",
|
||
"filtered_corr = train[features].corr()\n",
|
||
"\n",
|
||
"# 6. 히트맵 시각화\n",
|
||
"plt.figure(figsize=(15, 12))\n",
|
||
"sns.heatmap(data=filtered_corr, annot=True, cmap='coolwarm', fmt=\".2f\", linewidths=0.5)\n",
|
||
"plt.title(\"Filtered Feature Correlation Heatmap\", fontsize=14)\n",
|
||
"plt.xticks(rotation=90, fontsize=8)\n",
|
||
"plt.yticks(fontsize=8)\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 83,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.preprocessing import MinMaxScaler\n",
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# 1. URL_clean 제외\n",
|
||
"features = [col for col in train.columns if col != 'URL_clean']\n",
|
||
"X = train[features]\n",
|
||
"\n",
|
||
"# 2. 숫자형 컬럼만 선택\n",
|
||
"X_numeric = X.select_dtypes(include=['int64', 'float64'])\n",
|
||
"\n",
|
||
"# 3. 정규화\n",
|
||
"scaler = MinMaxScaler()\n",
|
||
"X_scaled = scaler.fit_transform(X_numeric)\n",
|
||
"\n",
|
||
"# 4. 희소 컬럼 제거 기준 계산\n",
|
||
"X_df = pd.DataFrame(X_scaled, columns=X_numeric.columns)\n",
|
||
"high_zero_cols = (X_df == 0).mean() > 0.9 # boolean mask (index = column names)\n",
|
||
"\n",
|
||
"# 5. 최종 학습용 피처\n",
|
||
"X_filtered = X_df.loc[:, ~high_zero_cols]\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 84,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# 1. X_test를 DataFrame으로 변환 (열 이름 맞춰야 함!)\n",
|
||
"X_test = pd.DataFrame(X_test, columns=X_numeric.columns)\n",
|
||
"\n",
|
||
"# 2. 정규화\n",
|
||
"X_test_scaled = scaler.transform(X_test)\n",
|
||
"\n",
|
||
"# 3. DataFrame으로 만들고, 희소 컬럼 제거\n",
|
||
"X_test_df = pd.DataFrame(X_test_scaled, columns=X_numeric.columns)\n",
|
||
"X_test_filtered = X_test_df.loc[:, ~high_zero_cols]\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 85,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"제거 전 shape: (6995056, 26)\n",
|
||
"제거 후 shape: (6995056, 15)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# 0의 비율이 90% 이상인 컬럼 제거\n",
|
||
"X_df = pd.DataFrame(X_scaled)\n",
|
||
"\n",
|
||
"high_zero_cols = (X_df == 0).mean() > 0.9\n",
|
||
"X_filtered = X_df.loc[:, ~high_zero_cols]\n",
|
||
"\n",
|
||
"print(f\"제거 전 shape: {X_df.shape}\")\n",
|
||
"print(f\"제거 후 shape: {X_filtered.shape}\")\n",
|
||
"\n",
|
||
"\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 86,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.model_selection import train_test_split\n",
|
||
"\n",
|
||
"# 1단계: 전체에서 테스트 세트 먼저 떼어내기 (20%)\n",
|
||
"X_train_full, X_test, y_train_full, y_test = train_test_split(\n",
|
||
" X_scaled, y, test_size=0.2, random_state=42, stratify=y\n",
|
||
")\n",
|
||
"\n",
|
||
"# 2단계: 남은 80% 중에서 훈련 / 검증으로 다시 나누기 (검증 20% = 전체의 16%)\n",
|
||
"X_train, X_val, y_train, y_val = train_test_split(\n",
|
||
" X_train_full, y_train_full, test_size=0.2, random_state=42, stratify=y_train_full)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 87,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"C:\\Users\\human\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\keras\\src\\layers\\core\\dense.py:87: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
|
||
" super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tensorflow.keras.models import Sequential\n",
|
||
"from tensorflow.keras.layers import Dense\n",
|
||
"# input_dim 자동 설정\n",
|
||
"model = Sequential()\n",
|
||
"model.add(Dense(64, input_dim=X_train.shape[1], activation='relu'))\n",
|
||
"model.add(Dense(32, activation='relu'))\n",
|
||
"model.add(Dense(1, activation='sigmoid'))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 88,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# 모델 컴파일\n",
|
||
"from tensorflow.keras.optimizers import Adam\n",
|
||
"\n",
|
||
"optimizer = Adam(learning_rate=0.001)\n",
|
||
"model.compile(optimizer=optimizer, loss='binary_crossentropy', metrics=['accuracy'])\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 89,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# EarlyStopping 콜백을 사용하여 검증 손실이 개선되지 않으면 학습을 멈추도록 설정\n",
|
||
"from tensorflow.keras.callbacks import EarlyStopping\n",
|
||
"early_stopping = EarlyStopping(monitor='val_loss', patience=100)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 90,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"label\n",
|
||
"0 3475301\n",
|
||
"1 1001534\n",
|
||
"Name: count, dtype: int64\n",
|
||
"label\n",
|
||
"0 868826\n",
|
||
"1 250383\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(y_train.value_counts())\n",
|
||
"print(y_val.value_counts())\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 91,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"최소값: 0.0\n",
|
||
"최대값: 1.0\n",
|
||
"평균값: 0.09535820033324473\n",
|
||
" 0 1 2 3 4 \\\n",
|
||
"count 6.995056e+06 6.995056e+06 6.995056e+06 6.995056e+06 6.995056e+06 \n",
|
||
"mean 2.237147e-01 9.073935e-03 8.184422e-04 2.416719e-03 1.001629e-03 \n",
|
||
"std 4.167331e-01 5.921112e-03 4.895222e-03 2.806215e-03 2.827064e-03 \n",
|
||
"min 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n",
|
||
"25% 0.000000e+00 5.847953e-03 0.000000e+00 1.451028e-03 0.000000e+00 \n",
|
||
"50% 0.000000e+00 5.847953e-03 0.000000e+00 1.934704e-03 0.000000e+00 \n",
|
||
"75% 0.000000e+00 1.169591e-02 0.000000e+00 2.660218e-03 0.000000e+00 \n",
|
||
"max 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 \n",
|
||
"\n",
|
||
" 5 6 7 8 9 \\\n",
|
||
"count 6.995056e+06 6.995056e+06 6.995056e+06 6.995056e+06 6.995056e+06 \n",
|
||
"mean 3.362564e-04 3.447601e-05 3.229334e-04 4.075875e-04 1.812709e-04 \n",
|
||
"std 4.442646e-03 2.974770e-03 2.734438e-03 2.554672e-03 4.495263e-03 \n",
|
||
"min 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n",
|
||
"25% 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n",
|
||
"50% 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n",
|
||
"75% 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n",
|
||
"max 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 \n",
|
||
"\n",
|
||
" ... 16 17 18 19 \\\n",
|
||
"count ... 6.995056e+06 6.995056e+06 6.995056e+06 6.995056e+06 \n",
|
||
"mean ... 5.781327e-01 5.401024e-01 3.071512e-02 6.304762e-03 \n",
|
||
"std ... 1.004096e-01 7.299464e-02 1.725448e-01 3.746718e-02 \n",
|
||
"min ... 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n",
|
||
"25% ... 5.029240e-01 4.940436e-01 0.000000e+00 0.000000e+00 \n",
|
||
"50% ... 5.029240e-01 5.348887e-01 0.000000e+00 0.000000e+00 \n",
|
||
"75% ... 6.705653e-01 5.801305e-01 0.000000e+00 0.000000e+00 \n",
|
||
"max ... 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 \n",
|
||
"\n",
|
||
" 20 21 22 23 24 \\\n",
|
||
"count 6.995056e+06 6.995056e+06 6.995056e+06 6.995056e+06 6.995056e+06 \n",
|
||
"mean 3.030183e-02 8.226073e-01 1.048126e-01 4.596937e-03 6.595001e-02 \n",
|
||
"std 8.574374e-02 9.365064e-02 4.395419e-02 1.206882e-02 2.481947e-01 \n",
|
||
"min 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n",
|
||
"25% 0.000000e+00 7.954145e-01 6.941138e-02 0.000000e+00 0.000000e+00 \n",
|
||
"50% 0.000000e+00 8.436214e-01 1.006465e-01 0.000000e+00 0.000000e+00 \n",
|
||
"75% 0.000000e+00 8.803006e-01 1.341953e-01 7.352941e-03 0.000000e+00 \n",
|
||
"max 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 \n",
|
||
"\n",
|
||
" 25 \n",
|
||
"count 6.995056e+06 \n",
|
||
"mean 1.968247e-03 \n",
|
||
"std 4.432125e-02 \n",
|
||
"min 0.000000e+00 \n",
|
||
"25% 0.000000e+00 \n",
|
||
"50% 0.000000e+00 \n",
|
||
"75% 0.000000e+00 \n",
|
||
"max 1.000000e+00 \n",
|
||
"\n",
|
||
"[8 rows x 26 columns]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# X_scaled가 넘파이 배열이라면\n",
|
||
"print(\"최소값:\", np.min(X_scaled))\n",
|
||
"print(\"최대값:\", np.max(X_scaled))\n",
|
||
"print(\"평균값:\", np.mean(X_scaled))\n",
|
||
"\n",
|
||
"# 또는\n",
|
||
"print(pd.DataFrame(X_scaled).describe())\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 106,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"X_val = pd.DataFrame(X_val, columns=X_numeric.columns)\n",
|
||
"# high_zero_cols를 X_val에 맞춰 정렬\n",
|
||
"high_zero_cols_aligned = high_zero_cols.reindex(X_val.columns, fill_value=False)\n",
|
||
"\n",
|
||
"# 재정렬된 기준으로 희소 컬럼 제거\n",
|
||
"X_val_filtered = X_val.loc[:, ~high_zero_cols_aligned]\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 108,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# 0이 많은 피처 제거 \n",
|
||
"X_df = pd.DataFrame(X_scaled)\n",
|
||
"high_zero_cols = (X_df == 0).mean() > 0.9\n",
|
||
"X_filtered = X_df.loc[:, ~high_zero_cols]\n",
|
||
"X_val = pd.DataFrame(X_val, columns=X_numeric.columns)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 109,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# 훈련데이터 /검증데이터 다시 나눔 \n",
|
||
"from sklearn.model_selection import train_test_split\n",
|
||
"\n",
|
||
"X_train, X_val, y_train, y_val = train_test_split(\n",
|
||
" X_filtered, y, test_size=0.2, random_state=42, stratify=y\n",
|
||
")\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 110,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# 가중치 계산 (불균형 보정)\n",
|
||
"\n",
|
||
"from sklearn.utils import class_weight\n",
|
||
"import numpy as np\n",
|
||
"\n",
|
||
"weights = class_weight.compute_class_weight(\n",
|
||
" class_weight='balanced',\n",
|
||
" classes=np.unique(y_train),\n",
|
||
" y=y_train\n",
|
||
")\n",
|
||
"class_weights = dict(zip(np.unique(y_train), weights))\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 111,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 600x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from collections import Counter\n",
|
||
"\n",
|
||
"# y_train의 클래스 분포 시각화\n",
|
||
"plt.figure(figsize=(6,4))\n",
|
||
"plt.bar(*zip(*Counter(y_train).items())) # y_train의 클래스 값과 빈도수로 막대 그래프\n",
|
||
"plt.xlabel('Class')\n",
|
||
"plt.ylabel('Frequency')\n",
|
||
"plt.title('Class Distribution in y_train')\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 115,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"After undersampling: Counter({0: 1251917, 1: 1251917})\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from imblearn.under_sampling import RandomUnderSampler\n",
|
||
"\n",
|
||
"# 언더샘플링 적용\n",
|
||
"rus = RandomUnderSampler(random_state=42)\n",
|
||
"\n",
|
||
"# X_train과 y_train을 언더샘플링하여 균형 맞추기\n",
|
||
"X_train_under, y_train_under = rus.fit_resample(X_train, y_train)\n",
|
||
"\n",
|
||
"# 언더샘플링 후 클래스 분포 확인\n",
|
||
"print(\"After undersampling:\", Counter(y_train_under))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 117,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 600x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# 언더샘플링 후 클래스 분포 시각화\n",
|
||
"plt.figure(figsize=(6,4))\n",
|
||
"plt.bar(*zip(*Counter(y_train_under).items())) # 이게 핵심!\n",
|
||
"plt.xlabel('Class')\n",
|
||
"plt.ylabel('Frequency')\n",
|
||
"plt.title('Class Distribution in y_train (after undersampling)')\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 120,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "ValueError",
|
||
"evalue": "Exception encountered when calling Sequential.call().\n\n\u001b[1mInput 0 of layer \"dense_9\" is incompatible with the layer: expected axis -1 of input shape to have value 26, but received input with shape (32, 15)\u001b[0m\n\nArguments received by Sequential.call():\n • inputs=tf.Tensor(shape=(32, 15), dtype=float32)\n • training=False\n • mask=None",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
||
"\u001b[31mValueError\u001b[39m Traceback (most recent call last)",
|
||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[120]\u001b[39m\u001b[32m, line 15\u001b[39m\n\u001b[32m 12\u001b[39m accuracies = []\n\u001b[32m 13\u001b[39m thresholds = []\n\u001b[32m---> \u001b[39m\u001b[32m15\u001b[39m y_val_proba = \u001b[43mmodel\u001b[49m\u001b[43m.\u001b[49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_val\u001b[49m\u001b[43m)\u001b[49m.flatten()\n\u001b[32m 17\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m thresholds:\n\u001b[32m 18\u001b[39m y_pred = (y_val_proba > t).astype(\u001b[38;5;28mint\u001b[39m) \u001b[38;5;66;03m# 임계값 기준으로 이진 분류\u001b[39;00m\n",
|
||
"\u001b[36mFile \u001b[39m\u001b[32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\keras\\src\\utils\\traceback_utils.py:122\u001b[39m, in \u001b[36mfilter_traceback.<locals>.error_handler\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 119\u001b[39m filtered_tb = _process_traceback_frames(e.__traceback__)\n\u001b[32m 120\u001b[39m \u001b[38;5;66;03m# To get the full stack trace, call:\u001b[39;00m\n\u001b[32m 121\u001b[39m \u001b[38;5;66;03m# `keras.config.disable_traceback_filtering()`\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m122\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m e.with_traceback(filtered_tb) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m 123\u001b[39m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[32m 124\u001b[39m \u001b[38;5;28;01mdel\u001b[39;00m filtered_tb\n",
|
||
"\u001b[36mFile \u001b[39m\u001b[32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\keras\\src\\layers\\input_spec.py:227\u001b[39m, in \u001b[36massert_input_compatibility\u001b[39m\u001b[34m(input_spec, inputs, layer_name)\u001b[39m\n\u001b[32m 222\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m axis, value \u001b[38;5;129;01min\u001b[39;00m spec.axes.items():\n\u001b[32m 223\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m value \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m shape[axis] \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m {\n\u001b[32m 224\u001b[39m value,\n\u001b[32m 225\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m 226\u001b[39m }:\n\u001b[32m--> \u001b[39m\u001b[32m227\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m 228\u001b[39m \u001b[33mf\u001b[39m\u001b[33m'\u001b[39m\u001b[33mInput \u001b[39m\u001b[38;5;132;01m{\u001b[39;00minput_index\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m of layer \u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mlayer_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\u001b[33m is \u001b[39m\u001b[33m'\u001b[39m\n\u001b[32m 229\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mincompatible with the layer: expected axis \u001b[39m\u001b[38;5;132;01m{\u001b[39;00maxis\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 230\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mof input shape to have value \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mvalue\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m, \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 231\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mbut received input with \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 232\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mshape \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 233\u001b[39m )\n\u001b[32m 234\u001b[39m \u001b[38;5;66;03m# Check shape.\u001b[39;00m\n\u001b[32m 235\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m spec.shape \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
|
||
"\u001b[31mValueError\u001b[39m: Exception encountered when calling Sequential.call().\n\n\u001b[1mInput 0 of layer \"dense_9\" is incompatible with the layer: expected axis -1 of input shape to have value 26, but received input with shape (32, 15)\u001b[0m\n\nArguments received by Sequential.call():\n • inputs=tf.Tensor(shape=(32, 15), dtype=float32)\n • training=False\n • mask=None"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.metrics import f1_score, accuracy_score\n",
|
||
"\n",
|
||
"# 확률 예측값이 y_val_proba라고 가정\n",
|
||
"# 예: y_val_proba = model.predict(X_val).ravel()\n",
|
||
"\n",
|
||
"# 0.1 ~ 0.89 범위에서 0.01 간격으로 threshold 후보 생성\n",
|
||
"thresholds = np.arange(0.1, 0.9, 0.01)\n",
|
||
"\n",
|
||
"# 각 threshold마다 F1 점수 계산\n",
|
||
"threshold_range = [i * 0.01 for i in range(100)]\n",
|
||
"f1_scores = []\n",
|
||
"accuracies = []\n",
|
||
"thresholds = []\n",
|
||
"\n",
|
||
"y_val_proba = model.predict(X_val).flatten()\n",
|
||
"\n",
|
||
"for t in thresholds:\n",
|
||
" y_pred = (y_val_proba > t).astype(int) # 임계값 기준으로 이진 분류\n",
|
||
" score = f1_score(y_val, y_pred)\n",
|
||
" f1_scores.append(score)\n",
|
||
" acc = accuracy_score(y_val, y_pred) \n",
|
||
"\n",
|
||
"for t in [i * 0.01 for i in range(100)]:\n",
|
||
" y_pred = (y_val_proba > t).astype(int)\n",
|
||
"\n",
|
||
" try:\n",
|
||
" f1 = f1_score(y_val, y_pred)\n",
|
||
" acc = accuracy_score(y_val, y_pred)\n",
|
||
"\n",
|
||
" thresholds.append(t) # 여기서 같이 append!\n",
|
||
" f1_scores.append(f1)\n",
|
||
" accuracies.append(acc)\n",
|
||
" except:\n",
|
||
" continue"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 69,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Best Threshold: 0.54\n",
|
||
"Best F1 Score: 0.9036\n",
|
||
"Accuracy at Best Threshold: 0.9583\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# 최고 F1 점수 기준 인덱스\n",
|
||
"best_idx = f1_scores.index(max(f1_scores))\n",
|
||
"best_threshold = thresholds[best_idx]\n",
|
||
"best_f1 = f1_scores[best_idx]\n",
|
||
"best_acc = accuracies[best_idx] \n",
|
||
"\n",
|
||
"print(f\"Best Threshold: {best_threshold:.2f}\")\n",
|
||
"\n",
|
||
"print(f\"Best F1 Score: {best_f1:.4f}\")\n",
|
||
"print(f\"Accuracy at Best Threshold: {best_acc:.4f}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 70,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 1000x500 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure(figsize=(10, 5))\n",
|
||
"plt.plot(thresholds, f1_scores, label='F1 Score', color='blue')\n",
|
||
"plt.plot(thresholds, accuracies, label='Accuracy', color='green')\n",
|
||
"plt.axvline(x=best_threshold, color='red', linestyle='--', label=f'Best Threshold: {best_threshold:0.33f}')\n",
|
||
"plt.xlabel(\"Threshold\")\n",
|
||
"plt.ylabel(\"Score\")\n",
|
||
"plt.title(\"F1 Score & Accuracy by Threshold\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid(True)\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 71,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "ValueError",
|
||
"evalue": "Exception encountered when calling Sequential.call().\n\n\u001b[1mInput 0 of layer \"dense_6\" is incompatible with the layer: expected axis -1 of input shape to have value 15, but received input with shape (32, 26)\u001b[0m\n\nArguments received by Sequential.call():\n • inputs=tf.Tensor(shape=(32, 26), dtype=float32)\n • training=False\n • mask=None",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
||
"\u001b[31mValueError\u001b[39m Traceback (most recent call last)",
|
||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[71]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m# 테스트 데이터 예측 확률\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m y_test_proba = \u001b[43mmodel\u001b[49m\u001b[43m.\u001b[49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_test\u001b[49m\u001b[43m)\u001b[49m.ravel()\n\u001b[32m 4\u001b[39m \u001b[38;5;66;03m# 최적 임계값 적용해서 예측값 변환\u001b[39;00m\n\u001b[32m 5\u001b[39m y_test_pred = (y_test_proba > best_threshold).astype(\u001b[38;5;28mint\u001b[39m)\n",
|
||
"\u001b[36mFile \u001b[39m\u001b[32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\keras\\src\\utils\\traceback_utils.py:122\u001b[39m, in \u001b[36mfilter_traceback.<locals>.error_handler\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 119\u001b[39m filtered_tb = _process_traceback_frames(e.__traceback__)\n\u001b[32m 120\u001b[39m \u001b[38;5;66;03m# To get the full stack trace, call:\u001b[39;00m\n\u001b[32m 121\u001b[39m \u001b[38;5;66;03m# `keras.config.disable_traceback_filtering()`\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m122\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m e.with_traceback(filtered_tb) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m 123\u001b[39m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[32m 124\u001b[39m \u001b[38;5;28;01mdel\u001b[39;00m filtered_tb\n",
|
||
"\u001b[36mFile \u001b[39m\u001b[32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\keras\\src\\layers\\input_spec.py:227\u001b[39m, in \u001b[36massert_input_compatibility\u001b[39m\u001b[34m(input_spec, inputs, layer_name)\u001b[39m\n\u001b[32m 222\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m axis, value \u001b[38;5;129;01min\u001b[39;00m spec.axes.items():\n\u001b[32m 223\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m value \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m shape[axis] \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m {\n\u001b[32m 224\u001b[39m value,\n\u001b[32m 225\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m 226\u001b[39m }:\n\u001b[32m--> \u001b[39m\u001b[32m227\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m 228\u001b[39m \u001b[33mf\u001b[39m\u001b[33m'\u001b[39m\u001b[33mInput \u001b[39m\u001b[38;5;132;01m{\u001b[39;00minput_index\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m of layer \u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mlayer_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\u001b[33m is \u001b[39m\u001b[33m'\u001b[39m\n\u001b[32m 229\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mincompatible with the layer: expected axis \u001b[39m\u001b[38;5;132;01m{\u001b[39;00maxis\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 230\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mof input shape to have value \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mvalue\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m, \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 231\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mbut received input with \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 232\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mshape \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 233\u001b[39m )\n\u001b[32m 234\u001b[39m \u001b[38;5;66;03m# Check shape.\u001b[39;00m\n\u001b[32m 235\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m spec.shape \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
|
||
"\u001b[31mValueError\u001b[39m: Exception encountered when calling Sequential.call().\n\n\u001b[1mInput 0 of layer \"dense_6\" is incompatible with the layer: expected axis -1 of input shape to have value 15, but received input with shape (32, 26)\u001b[0m\n\nArguments received by Sequential.call():\n • inputs=tf.Tensor(shape=(32, 26), dtype=float32)\n • training=False\n • mask=None"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# 테스트 데이터 예측 확률\n",
|
||
"y_test_proba = model.predict(X_test).ravel()\n",
|
||
"\n",
|
||
"# 최적 임계값 적용해서 예측값 변환\n",
|
||
"y_test_pred = (y_test_proba > best_threshold).astype(int)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\u001b[1m43720/43720\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 700us/step\n",
|
||
"Test Accuracy: 0.22371502174391641\n",
|
||
"Test ROC AUC: 0.9128971739854275\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"y_test_pred = model.predict(X_test) # 테스트 데이터에 대해 예측\n",
|
||
"y_test_pred = (y_test_pred > 0.3).astype(int) # 이진 분류이므로 0.5를 기준으로 0과 1로 변환\n",
|
||
"\n",
|
||
"# 성능 평가\n",
|
||
"from sklearn.metrics import accuracy_score, roc_auc_score\n",
|
||
"\n",
|
||
"print(\"Test Accuracy:\", accuracy_score(y_test, y_test_pred))\n",
|
||
"print(\"Test ROC AUC:\", roc_auc_score(y_test, y_test_proba))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# 모델 평가\n",
|
||
"from sklearn.metrics import accuracy_score\n",
|
||
"val_loss, val_accuracy = model.evaluate(X_val_filtered, y_val)\n",
|
||
"print(f'Validation Accuracy: {val_accuracy:.4f}')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Epoch 1/5\n",
|
||
"\u001b[1m139902/139902\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m226s\u001b[0m 2ms/step - accuracy: 0.9956 - loss: 0.0169 - val_accuracy: 1.0000 - val_loss: 1.3147e-09\n",
|
||
"Epoch 2/5\n",
|
||
"\u001b[1m139902/139902\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m222s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 1.2477e-09 - val_accuracy: 1.0000 - val_loss: 1.0591e-09\n",
|
||
"Epoch 3/5\n",
|
||
"\u001b[1m139902/139902\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m224s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 1.0335e-09 - val_accuracy: 1.0000 - val_loss: 9.4072e-10\n",
|
||
"Epoch 4/5\n",
|
||
"\u001b[1m139902/139902\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m232s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 9.2705e-10 - val_accuracy: 1.0000 - val_loss: 8.7052e-10\n",
|
||
"Epoch 5/5\n",
|
||
"\u001b[1m139902/139902\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m226s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 8.5948e-10 - val_accuracy: 1.0000 - val_loss: 8.1871e-10\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.utils import class_weight\n",
|
||
"import numpy as np\n",
|
||
"\n",
|
||
"\n",
|
||
"class_weights = dict(zip(np.unique(y_train), weights))\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"# 모델 학습 (Epoch마다 정확도 출력)\n",
|
||
"history = model.fit(X_train, y_train, \n",
|
||
" epochs=5, # 최대 epoch 수\n",
|
||
" batch_size=256, # 배치 크기\n",
|
||
" validation_data=(X_val, y_val), # 검증 데이터\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Classification Report:\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"C:\\Users\\human\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\sklearn\\metrics\\_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
|
||
" _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n",
|
||
"C:\\Users\\human\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\sklearn\\metrics\\_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
|
||
" _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n",
|
||
"C:\\Users\\human\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\sklearn\\metrics\\_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
|
||
" _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" precision recall f1-score support\n",
|
||
"\n",
|
||
" 0 0.78 1.00 0.87 868826\n",
|
||
" 1 0.00 0.00 0.00 250383\n",
|
||
"\n",
|
||
" accuracy 0.78 1119209\n",
|
||
" macro avg 0.39 0.50 0.44 1119209\n",
|
||
"weighted avg 0.60 0.78 0.68 1119209\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.metrics import classification_report, ConfusionMatrixDisplay\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"# 평가 지표 출력\n",
|
||
"print(\"Classification Report:\\n\")\n",
|
||
"print(classification_report(y_val, y_pred))\n",
|
||
"\n",
|
||
"# 혼동 행렬 시각화\n",
|
||
"ConfusionMatrixDisplay.from_predictions(y_val, y_pred, cmap='Blues')\n",
|
||
"plt.title(\"Confusion Matrix\")\n",
|
||
"plt.show()\n"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.11.9"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|