Fake News Detection.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c740dd4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "45f675dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv(\"/Users/ayyappatata/Desktop/Project/Datasets/main dataset/data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "d12ddc1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>URLs</th>\n",
       "      <th>Headline</th>\n",
       "      <th>Body</th>\n",
       "      <th>Label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>http://www.bbc.com/news/world-us-canada-414191...</td>\n",
       "      <td>Four ways Bob Corker skewered Donald Trump</td>\n",
       "      <td>Image copyright Getty Images\\nOn Sunday mornin...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://www.reuters.com/article/us-filmfestiva...</td>\n",
       "      <td>Linklater's war veteran comedy speaks to moder...</td>\n",
       "      <td>LONDON (Reuters) - “Last Flag Flying”, a comed...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://www.nytimes.com/2017/10/09/us/politics...</td>\n",
       "      <td>Trump’s Fight With Corker Jeopardizes His Legi...</td>\n",
       "      <td>The feud broke into public view last week when...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://www.reuters.com/article/us-mexico-oil-...</td>\n",
       "      <td>Egypt's Cheiron wins tie-up with Pemex for Mex...</td>\n",
       "      <td>MEXICO CITY (Reuters) - Egypt’s Cheiron Holdin...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>http://www.cnn.com/videos/cnnmoney/2017/10/08/...</td>\n",
       "      <td>Jason Aldean opens 'SNL' with Vegas tribute</td>\n",
       "      <td>Country singer Jason Aldean, who was performin...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                URLs  \\\n",
       "0  http://www.bbc.com/news/world-us-canada-414191...   \n",
       "1  https://www.reuters.com/article/us-filmfestiva...   \n",
       "2  https://www.nytimes.com/2017/10/09/us/politics...   \n",
       "3  https://www.reuters.com/article/us-mexico-oil-...   \n",
       "4  http://www.cnn.com/videos/cnnmoney/2017/10/08/...   \n",
       "\n",
       "                                            Headline  \\\n",
       "0         Four ways Bob Corker skewered Donald Trump   \n",
       "1  Linklater's war veteran comedy speaks to moder...   \n",
       "2  Trump’s Fight With Corker Jeopardizes His Legi...   \n",
       "3  Egypt's Cheiron wins tie-up with Pemex for Mex...   \n",
       "4        Jason Aldean opens 'SNL' with Vegas tribute   \n",
       "\n",
       "                                                Body  Label  \n",
       "0  Image copyright Getty Images\\nOn Sunday mornin...      1  \n",
       "1  LONDON (Reuters) - “Last Flag Flying”, a comed...      1  \n",
       "2  The feud broke into public view last week when...      1  \n",
       "3  MEXICO CITY (Reuters) - Egypt’s Cheiron Holdin...      1  \n",
       "4  Country singer Jason Aldean, who was performin...      1  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12d6a46d",
   "metadata": {},
   "source": [
    "# Data pre-processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "bfd91aae",
   "metadata": {},
   "outputs": [],
   "source": [
    "X=df.drop('Label',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "04bd72d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>URLs</th>\n",
       "      <th>Headline</th>\n",
       "      <th>Body</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>http://www.bbc.com/news/world-us-canada-414191...</td>\n",
       "      <td>Four ways Bob Corker skewered Donald Trump</td>\n",
       "      <td>Image copyright Getty Images\\nOn Sunday mornin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://www.reuters.com/article/us-filmfestiva...</td>\n",
       "      <td>Linklater's war veteran comedy speaks to moder...</td>\n",
       "      <td>LONDON (Reuters) - “Last Flag Flying”, a comed...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://www.nytimes.com/2017/10/09/us/politics...</td>\n",
       "      <td>Trump’s Fight With Corker Jeopardizes His Legi...</td>\n",
       "      <td>The feud broke into public view last week when...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://www.reuters.com/article/us-mexico-oil-...</td>\n",
       "      <td>Egypt's Cheiron wins tie-up with Pemex for Mex...</td>\n",
       "      <td>MEXICO CITY (Reuters) - Egypt’s Cheiron Holdin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>http://www.cnn.com/videos/cnnmoney/2017/10/08/...</td>\n",
       "      <td>Jason Aldean opens 'SNL' with Vegas tribute</td>\n",
       "      <td>Country singer Jason Aldean, who was performin...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                URLs  \\\n",
       "0  http://www.bbc.com/news/world-us-canada-414191...   \n",
       "1  https://www.reuters.com/article/us-filmfestiva...   \n",
       "2  https://www.nytimes.com/2017/10/09/us/politics...   \n",
       "3  https://www.reuters.com/article/us-mexico-oil-...   \n",
       "4  http://www.cnn.com/videos/cnnmoney/2017/10/08/...   \n",
       "\n",
       "                                            Headline  \\\n",
       "0         Four ways Bob Corker skewered Donald Trump   \n",
       "1  Linklater's war veteran comedy speaks to moder...   \n",
       "2  Trump’s Fight With Corker Jeopardizes His Legi...   \n",
       "3  Egypt's Cheiron wins tie-up with Pemex for Mex...   \n",
       "4        Jason Aldean opens 'SNL' with Vegas tribute   \n",
       "\n",
       "                                                Body  \n",
       "0  Image copyright Getty Images\\nOn Sunday mornin...  \n",
       "1  LONDON (Reuters) - “Last Flag Flying”, a comed...  \n",
       "2  The feud broke into public view last week when...  \n",
       "3  MEXICO CITY (Reuters) - Egypt’s Cheiron Holdin...  \n",
       "4  Country singer Jason Aldean, who was performin...  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "678640ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=df['Label']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "01823fca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    1\n",
       "2    1\n",
       "3    1\n",
       "4    1\n",
       "Name: Label, dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "d8ca182a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4009, 4)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84f8b522",
   "metadata": {},
   "source": [
    "# Feature Extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "7d5467ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "413adf6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "e706dee9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3988, 4)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "5fb0e683",
   "metadata": {},
   "outputs": [],
   "source": [
    "messages=df.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "41df4185",
   "metadata": {},
   "outputs": [],
   "source": [
    "messages.reset_index(inplace=True)#index reset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "ff53fa38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>index</th>\n",
       "      <th>URLs</th>\n",
       "      <th>Headline</th>\n",
       "      <th>Body</th>\n",
       "      <th>Label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>http://www.bbc.com/news/world-us-canada-414191...</td>\n",
       "      <td>Four ways Bob Corker skewered Donald Trump</td>\n",
       "      <td>Image copyright Getty Images\\nOn Sunday mornin...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>https://www.reuters.com/article/us-filmfestiva...</td>\n",
       "      <td>Linklater's war veteran comedy speaks to moder...</td>\n",
       "      <td>LONDON (Reuters) - “Last Flag Flying”, a comed...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>https://www.nytimes.com/2017/10/09/us/politics...</td>\n",
       "      <td>Trump’s Fight With Corker Jeopardizes His Legi...</td>\n",
       "      <td>The feud broke into public view last week when...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>https://www.reuters.com/article/us-mexico-oil-...</td>\n",
       "      <td>Egypt's Cheiron wins tie-up with Pemex for Mex...</td>\n",
       "      <td>MEXICO CITY (Reuters) - Egypt’s Cheiron Holdin...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>http://www.cnn.com/videos/cnnmoney/2017/10/08/...</td>\n",
       "      <td>Jason Aldean opens 'SNL' with Vegas tribute</td>\n",
       "      <td>Country singer Jason Aldean, who was performin...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>http://beforeitsnews.com/sports/2017/09/jetnat...</td>\n",
       "      <td>JetNation FanDuel League; Week 4</td>\n",
       "      <td>JetNation FanDuel League; Week 4\\n% of readers...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>https://www.nytimes.com/2017/10/10/us/politics...</td>\n",
       "      <td>Kansas Tried a Tax Plan Similar to Trump’s. It...</td>\n",
       "      <td>In 2012, Kansas lawmakers, led by Gov. Sam Bro...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>https://www.reuters.com/article/us-india-cenba...</td>\n",
       "      <td>India RBI chief: growth important, but not at ...</td>\n",
       "      <td>The Reserve Bank of India (RBI) Governor Urjit...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>https://www.reuters.com/article/us-climatechan...</td>\n",
       "      <td>EPA chief to sign rule on Clean Power Plan exi...</td>\n",
       "      <td>Scott Pruitt, Administrator of the U.S. Enviro...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index                                               URLs  \\\n",
       "0      0  http://www.bbc.com/news/world-us-canada-414191...   \n",
       "1      1  https://www.reuters.com/article/us-filmfestiva...   \n",
       "2      2  https://www.nytimes.com/2017/10/09/us/politics...   \n",
       "3      3  https://www.reuters.com/article/us-mexico-oil-...   \n",
       "4      4  http://www.cnn.com/videos/cnnmoney/2017/10/08/...   \n",
       "5      5  http://beforeitsnews.com/sports/2017/09/jetnat...   \n",
       "6      6  https://www.nytimes.com/2017/10/10/us/politics...   \n",
       "7      7  https://www.reuters.com/article/us-india-cenba...   \n",
       "8      8  https://www.reuters.com/article/us-climatechan...   \n",
       "\n",
       "                                            Headline  \\\n",
       "0         Four ways Bob Corker skewered Donald Trump   \n",
       "1  Linklater's war veteran comedy speaks to moder...   \n",
       "2  Trump’s Fight With Corker Jeopardizes His Legi...   \n",
       "3  Egypt's Cheiron wins tie-up with Pemex for Mex...   \n",
       "4        Jason Aldean opens 'SNL' with Vegas tribute   \n",
       "5                   JetNation FanDuel League; Week 4   \n",
       "6  Kansas Tried a Tax Plan Similar to Trump’s. It...   \n",
       "7  India RBI chief: growth important, but not at ...   \n",
       "8  EPA chief to sign rule on Clean Power Plan exi...   \n",
       "\n",
       "                                                Body  Label  \n",
       "0  Image copyright Getty Images\\nOn Sunday mornin...      1  \n",
       "1  LONDON (Reuters) - “Last Flag Flying”, a comed...      1  \n",
       "2  The feud broke into public view last week when...      1  \n",
       "3  MEXICO CITY (Reuters) - Egypt’s Cheiron Holdin...      1  \n",
       "4  Country singer Jason Aldean, who was performin...      1  \n",
       "5  JetNation FanDuel League; Week 4\\n% of readers...      0  \n",
       "6  In 2012, Kansas lawmakers, led by Gov. Sam Bro...      1  \n",
       "7  The Reserve Bank of India (RBI) Governor Urjit...      1  \n",
       "8  Scott Pruitt, Administrator of the U.S. Enviro...      1  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "messages.head(9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "e6200013",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'MEXICO CITY (Reuters) - Egypt’s Cheiron Holdings Limited won the rights to partner with Mexican national oil company Pemex on its onshore Cardenas-Mora project, the industry regulator said on Wednesday.\\nThe tie-up marks only the second joint venture between the Pemex and a equity partner since an energy opening finalized in 2014 ended the company’s decades-long monopoly and allowed it to develop projects with private and foreign oil companies.\\nCardenas-Mora is a 65-square-mile (168 sq km) field located in Tabasco state believed to contain 93 million barrels of oil equivalent (boe) in proven, probable and possible reserves.'"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "messages['Body'][3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37937e30",
   "metadata": {},
   "source": [
    "# Text Preprocessing "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "6a36a8ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.corpus import stopwords\n",
    "from nltk.stem.porter import PorterStemmer\n",
    "import re\n",
    "ps = PorterStemmer()\n",
    "corpus = []\n",
    "for i in range(0, len(messages)):\n",
    "    review = re.sub('[^a-zA-Z]', ' ', messages['Body'][i])\n",
    "    review = review.lower()\n",
    "    review = review.split()\n",
    "    \n",
    "    review = [ps.stem(word) for word in review if not word in stopwords.words('english')]\n",
    "    review = ' '.join(review)\n",
    "    corpus.append(review)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "d27b523e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'mexico citi reuter egypt cheiron hold limit right partner mexican nation oil compani pemex onshor cardena mora project industri regul said wednesday tie mark second joint ventur pemex equiti partner sinc energi open final end compani decad long monopoli allow develop project privat foreign oil compani cardena mora squar mile sq km field locat tabasco state believ contain million barrel oil equival boe proven probabl possibl reserv'"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corpus[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "198e5638",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "tfidf_v=TfidfVectorizer(max_features=5000,ngram_range=(1,3))\n",
    "X=tfidf_v.fit_transform(corpus).toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "fe249ff8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3988, 5000)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "96f70a17",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0. 0. 0. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " ...\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]\n",
      " [0. 0. 0. ... 0. 0. 0.]]\n"
     ]
    }
   ],
   "source": [
    "print(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "2fc95538",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=messages['Label']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2df18f8",
   "metadata": {},
   "source": [
    "# Dividing the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "fbd0784d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "7cdfd61f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['aaron', 'aaron judg', 'aaron kesel', 'aaron rodger', 'ab',\n",
       "       'abandon', 'abc', 'abe', 'aberti', 'abil', 'abl', 'abort',\n",
       "       'abroad', 'absenc', 'absolut', 'abus', 'ac', 'academ', 'academi',\n",
       "       'acc'], dtype=object)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tfidf_v.get_feature_names_out()[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "81221482",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'analyzer': 'word',\n",
       " 'binary': False,\n",
       " 'decode_error': 'strict',\n",
       " 'dtype': numpy.float64,\n",
       " 'encoding': 'utf-8',\n",
       " 'input': 'content',\n",
       " 'lowercase': True,\n",
       " 'max_df': 1.0,\n",
       " 'max_features': 5000,\n",
       " 'min_df': 1,\n",
       " 'ngram_range': (1, 3),\n",
       " 'norm': 'l2',\n",
       " 'preprocessor': None,\n",
       " 'smooth_idf': True,\n",
       " 'stop_words': None,\n",
       " 'strip_accents': None,\n",
       " 'sublinear_tf': False,\n",
       " 'token_pattern': '(?u)\\\\b\\\\w\\\\w+\\\\b',\n",
       " 'tokenizer': None,\n",
       " 'use_idf': True,\n",
       " 'vocabulary': None}"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tfidf_v.get_params()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "d8aefd36",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.9/site-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.\n",
      "  warnings.warn(msg, category=FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "count_df = pd.DataFrame(X_train, columns=tfidf_v.get_feature_names())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "28d90b8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>aaron</th>\n",
       "      <th>aaron judg</th>\n",
       "      <th>aaron kesel</th>\n",
       "      <th>aaron rodger</th>\n",
       "      <th>ab</th>\n",
       "      <th>abandon</th>\n",
       "      <th>abc</th>\n",
       "      <th>abe</th>\n",
       "      <th>aberti</th>\n",
       "      <th>abil</th>\n",
       "      <th>...</th>\n",
       "      <th>yorker</th>\n",
       "      <th>young</th>\n",
       "      <th>younger</th>\n",
       "      <th>youth</th>\n",
       "      <th>youtub</th>\n",
       "      <th>zach</th>\n",
       "      <th>zapatista</th>\n",
       "      <th>zealand</th>\n",
       "      <th>zero</th>\n",
       "      <th>zone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.073735</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 5000 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      aaron  aaron judg  aaron kesel  aaron rodger   ab  abandon  abc  abe  \\\n",
       "0  0.073735         0.0          0.0           0.0  0.0      0.0  0.0  0.0   \n",
       "1  0.000000         0.0          0.0           0.0  0.0      0.0  0.0  0.0   \n",
       "2  0.000000         0.0          0.0           0.0  0.0      0.0  0.0  0.0   \n",
       "3  0.000000         0.0          0.0           0.0  0.0      0.0  0.0  0.0   \n",
       "4  0.000000         0.0          0.0           0.0  0.0      0.0  0.0  0.0   \n",
       "\n",
       "   aberti  abil  ...  yorker  young  younger  youth  youtub  zach  zapatista  \\\n",
       "0     0.0   0.0  ...     0.0    0.0      0.0    0.0     0.0   0.0        0.0   \n",
       "1     0.0   0.0  ...     0.0    0.0      0.0    0.0     0.0   0.0        0.0   \n",
       "2     0.0   0.0  ...     0.0    0.0      0.0    0.0     0.0   0.0        0.0   \n",
       "3     0.0   0.0  ...     0.0    0.0      0.0    0.0     0.0   0.0        0.0   \n",
       "4     0.0   0.0  ...     0.0    0.0      0.0    0.0     0.0   0.0        0.0   \n",
       "\n",
       "   zealand  zero  zone  \n",
       "0      0.0   0.0   0.0  \n",
       "1      0.0   0.0   0.0  \n",
       "2      0.0   0.0   0.0  \n",
       "3      0.0   0.0   0.0  \n",
       "4      0.0   0.0   0.0  \n",
       "\n",
       "[5 rows x 5000 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "2692d548",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4965077c",
   "metadata": {},
   "source": [
    "# Confusion Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "9b53ea3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_confusion_matrix(cm, classes,\n",
    "                          normalize=False,\n",
    "                          title='Confusion matrix',\n",
    "                          cmap=plt.cm.Blues):\n",
    "    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
    "    plt.title(title)\n",
    "    plt.colorbar()\n",
    "    tick_marks = np.arange(len(classes))\n",
    "    plt.xticks(tick_marks, classes, rotation=45)\n",
    "    plt.yticks(tick_marks, classes)\n",
    "\n",
    "    if normalize:\n",
    "        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
    "        print(\"Normalized confusion matrix\")\n",
    "    else:\n",
    "        print('Confusion matrix, without normalization')\n",
    "\n",
    "    thresh = cm.max() / 2.\n",
    "    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "        plt.text(j, i, cm[i, j],\n",
    "                 horizontalalignment=\"center\",\n",
    "                 color=\"white\" if cm[i, j] > thresh else \"black\")\n",
    "\n",
    "    plt.tight_layout()\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9db499a7",
   "metadata": {},
   "source": [
    "# Model Selection and building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "84fd66ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.naive_bayes import MultinomialNB\n",
    "classifier=MultinomialNB()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "0e414a97",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import metrics\n",
    "import numpy as np\n",
    "import itertools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "1a836eb9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy:   0.893\n",
      "Confusion matrix, without normalization\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAVAAAAEmCAYAAAA0k8gFAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAkQUlEQVR4nO3debzVVb3/8df7gBxU1B/IICrgEGaoOZtDGaklTmFdTZSMzFIL05ua1ymnomtWWqlkmrcoB0RNwQk1lat2NQVzAkVRHAhkckZEhs/vj+86uEXO3vtszj77uznvp4/v43z3d/xsjnxY37XWdy1FBGZm1nINtQ7AzKxeOYGamVXICdTMrEJOoGZmFXICNTOrkBOomVmFnECtWZLWlHSrpLcl3bAK1xkq6e7WjK1WJH1B0tRax2H5IPcDrX+SjgBOArYE3gWeAEZExEOreN0jgR8Cu0fEklWNM+8kBdA/IqbVOharDy6B1jlJJwG/AX4O9AL6AiOBwa1w+X7A8+0heZZDUsdax2A5ExFe6nQB1gPeAw4tckwjWYKdmZbfAI1p30BgBnAyMAeYBRyV9p0HfAgsTvc4GjgXuLrg2psAAXRMn78NvERWCp4ODC3Y/lDBebsDjwFvp5+7F+ybAPwU+Ee6zt1A92a+W1P8pxbEfzCwP/A88AZwRsHxuwAPA2+lYy8FOqV9D6TvsiB938MKrv9fwOvAX5u2pXM2T/fYIX3eEJgHDKz1/xte2mZxCbS+7QZ0Bm4ucsyZwK7AdsC2ZEnkrIL9G5Al4o3IkuRlkrpGxDlkpdrrI6JLRFxVLBBJawO/A/aLiHXIkuQTKzmuG3B7OnZ94CLgdknrFxx2BHAU0BPoBJxS5NYbkP0ZbAScDVwJfBPYEfgCcLakzdKxS4EfAd3J/uz2Bn4AEBF7pmO2Td/3+oLrdyMrjR9TeOOIeJEsuV4jaS3gT8CfI2JCkXhtNeIEWt/WB+ZF8UfsocD5ETEnIuaSlSyPLNi/OO1fHBF3kJW+Pl1hPMuArSWtGRGzImLySo45AHghIv4aEUsi4jrgOeCggmP+FBHPR8RCYAxZ8m/OYrL63sXAaLLk+NuIeDfdfzLwWYCImBQRj6T7vgz8AfhiGd/pnIhYlOL5mIi4EngB+CfQm+wfLGsnnEDr23yge4m6uQ2BVwo+v5K2Lb/GCgn4faBLSwOJiAVkj73HAbMk3S5pyzLiaYppo4LPr7cgnvkRsTStNyW42QX7FzadL2kLSbdJel3SO2Ql7O5Frg0wNyI+KHHMlcDWwCURsajEsbYacQKtbw8DH5DV+zVnJtnjZ5O+aVslFgBrFXzeoHBnRNwVEV8mK4k9R5ZYSsXTFNO/K4ypJX5PFlf/iFgXOANQiXOKdlOR1IWsXvkq4NxURWHthBNoHYuIt8nq/S6TdLCktSStIWk/SRemw64DzpLUQ1L3dPzVFd7yCWBPSX0lrQec3rRDUi9JX011oYvIqgKWruQadwBbSDpCUkdJhwEDgNsqjKkl1gHeAd5LpePvr7B/NrDZJ84q7rfApIj4Llnd7uWrHKXVDSfQOhcRF5H1AT0LmAu8BhwP3JIO+RkwEXgKeBp4PG2r5F73ANena03i40mvgaw1fyZZy/QXSQ00K1xjPnBgOnY+WQv6gRExr5KYWugUsgaqd8lKx9evsP9cYJSktyR9o9TFJA0GBpFVW0D2e9hB0tBWi9hyzR3pzcwq5BKomVmFnEDNzCrkBGpmViEnUDOzCq22gyOo45qhxnVrHYa1wJabb1j6IMuVmTNe5a035pfqS9siHdbtF7HkEy99fUIsnHtXRAxqzXu31OqbQBvXpXGAe5PUk2tuPLfWIVgLDT2o1JuwLRdLPqBxyyElj/vgX5eUeous6lbbBGpmdUqAWrVQWzVOoGaWP6qP5hknUDPLH5dAzcwqIZdAzcwqIqChQ62jKIsTqJnljPwIb2ZWMT/Cm5lVyCVQM7NKuBHJzKwybkQyM6uUS6BmZpVrcB2omVnLCZdAzcwq5lZ4M7NKuA7UzKxyboU3M6uA/CqnmVnl/AhvZlYhl0DNzCrhRiQzs8q5BGpmVgEJGuojNdVHlGbWvrgEamZWIdeBmplVyCVQM7MKyK3wZmaVcwnUzKzlBDQ0uARqZtZySksdcAI1s5wRqpNH+PooJ5tZuyKp5FLmdV6W9LSkJyRNTNu6SbpH0gvpZ9eC40+XNE3SVEn7lrq+E6iZ5U5rJdDkSxGxXUTslD6fBtwbEf2Be9NnJA0AhgBbAYOAkZKKDkzqBGpmudPKCXRFg4FRaX0UcHDB9tERsSgipgPTgF2KXcgJ1MxyRRJqKL0A3SVNLFiOWcnlArhb0qSC/b0iYhZA+tkzbd8IeK3g3BlpW7PciGRmuVNmCXNewWN5c/aIiJmSegL3SHqu2G1Xsi2KXdwlUDPLndZ6hI+ImennHOBmskfy2ZJ6p/v0Buakw2cAfQpO3xiYWez6TqBmljutkUAlrS1pnaZ14CvAM8A4YFg6bBgwNq2PA4ZIapS0KdAfeLTYPfwIb2b50nod6XsBN6dk2xG4NiLGS3oMGCPpaOBV4FCAiJgsaQwwBVgCDI+IpcVu4ARqZrki1CqvckbES8C2K9k+H9i7mXNGACPKvYcTqJnlTr28ieQEamb5Ux/50wnUzHJGLoGamVXMCdTMrEJOoGZmFRDLX9XMPSdQM8sX14Haqnhu7Fm8+/4ili5bxpIly/j8sIv57BYbcslph9LY2JElS5bxn7+4iYlTXmWnAX259MxDgexf7hFX3sW4CU/X+Bu0L+f+eDgP3jeebuv34Ia7HwFg5K9/xoR77qBBDXTr3p3zfvV7evTqzVtvvsGp3/8Wk596nIMOOYLTzv9VjaPPJydQWyWDjhvJ/LcXLP884ocHMeKPd3H3/z3Hvrt/hhEnHMi+x41k8ouz2ONbF7N06TI2WH8d/nntKdz+4GSWLl1Ww+jbl4MOOYLDhn2Ps086bvm2bx1zAj84+SwArvvT5Vzx219w5s9/Q2NjI98/+UxenDqFac8/W6uQc69eEqjfha8TEcG6a3cGYL0unZk19x0AFi5avDxZNjauQRQdO8aqYcfP7cF663X92LYu66y7fH3h+wuWJ4Q111qb7XfejU6Nnds0xrqjMpYccAk0hyKCWy89lojgqpsf5n9ufoQfX3QLt15yLP994kE0qIEvHf275cfvvFVfLj97CH036MrR51zr0mdOXPrL87n9b6Ppss66XHHdbbUOp664BApIWprmImlaNknbfyTpA0nrFRw7UNJtBZ9/JumuNDLKhDRHSdN1bqxm3LW213cvYfcjL+LgE6/k2EM+zx7bb8Yx/7EHp140lv4H/pRTL76F3//ksOXHPzb5VXY87EI+P+xifvztvWns5H8X8+D4H5/NnQ9PYb/BhzJ61BW1DqduSNm78KWWPKh2FAvTXCRNy8tp++HAY8DXVnaSpDOBPYCDI2JR2jy04DqHVDnumpo1L3s8n/vme4yb8DQ7b9WXoQfuxC33PwXATX9/kp0G9P3EeVNfnsOChR+y1eYbtGm8VtygwYdy3/hxtQ6jrlR5So9W0+ZpXNLmQBfgLLJEuuL+k4H9gYMiYmEbh1dza3XuRJe1Gpev77PrFkx+8XVmzX2HL+ywOQADd+7PtNfmAtBvw2506JD9Gvtu0JUt+vXglZlv1iZ4W+7V6S8uX3/g73eyyeb9axhNHXIdKABrSnoirU+PiK+RJc3rgAeBT0vqmUaLhqzU+Wlgx4h4b4VrXSOpKaHeExE/XvFmac6TbN6TTuu06hdpKz3X78L1F34HgI4dG7h+/OPc8/BzDH9/Eb88+WA6dujAog8Xc/zPbwBg92035ZRv783iJUtZtiw48Rc3faz13qrv9B9+h0mPPMRbb85n0K6f4bgfnc5D99/NKy9NQw0N9N6oD2eOuHj58QfssQ0L3nuHxYsXM+Hu2xn515vZrP+WNfwG+ZOXEmYpiio220p6LyK6rLDtGeBrEfGCpIuAFyPiMkkDgV8CXYHTIuLGgnMmAKdExMRy792wdq9oHDC0Fb6FtZX/u/HcWodgLTT0oC8y5al/tWq2a9ygf2w89Hclj3vpov0nlTEnUlW1aWuDpM+SDZN/T/oXphPwEnBZOmQ2MBS4V9L8iLi/LeMzs9oTUCcF0DavAz0cODciNknLhsBGkvo1HRARzwNfB66WtF0bx2dmNScaGkovedDW/V2GAPutsO3mtP2fTRsi4jFJRwHjJH0pbS6sA50XEftUPVozq4l6qQOtagJdsf4zIjZdyTEnFXycULD9bqCpr87AKoRnZnmk+nmEd49rM8sVQW4e0UtxAjWz3HEJ1MysQq4DNTOrgORHeDOzCuXnXfdSnEDNLHfqJH86gZpZ/rgEamZWiTrqB5qPUUnNzJKmfqCt9SqnpA6S/tU0YLukbpLukfRC+tm14NjTJU1LA7jvW+raTqBmljutPKDyiUDhDH6nAfdGRH/g3vQZSQPIXivfChgEjJTUodiFnUDNLHek0kt519HGwAHAHws2DwZGpfVRwMEF20dHxKKImA5MA3Ypdn0nUDPLF7VqCfQ3wKlA4UyLvSJiFkD62TNt3wh4reC4GWlbs5xAzSxXmsYDLaME2l3SxILlmI9dRzoQmBMRk1pw6xUVHXHerfBmljNllzDnlRiRfg/gq5L2BzoD60q6GpgtqXdEzJLUG2iaUmgG0Kfg/I2BmcUCcAnUzHKnNVrhI+L0iNg4IjYhaxy6LyK+CYwDhqXDhgFj0/o4YEiaSn1TstkzHi12D5dAzSxfqt8P9AJgjKSjgVeBQwEiYrKkMcAUYAkwPCKWFruQE6iZ5UpWB9q6GTQiJpAGbI+I+cDezRw3AhhR7nWdQM0sd/wqp5lZheokfzqBmln+uARqZlYBKT/TFpfiBGpmuVMnBVAnUDPLn4Y6yaBOoGaWO3WSP51AzSxfJDcimZlVrE7akJxAzSx/6r4VXtIlFBnKKSJOqEpEZtauCdBKR5bLn2Il0IltFoWZWYE6KYA2n0AjYlThZ0lrR8SC6odkZu1ay+c8qpmS44FK2k3SFNKkTJK2lTSy6pGZWbvVWnMiVVs5Ayr/BtgXmA8QEU8Ce1YxJjNrxwR0aFDJJQ/KaoWPiNdWKFIXHWTUzGxV1MsjfDkJ9DVJuwMhqRNwAh+fY9nMrNXk6RG9lHIS6HHAb8mm9/w3cBcwvJpBmVn7ttq8Cx8R84ChbRCLmRmw8vmF86icVvjNJN0qaa6kOZLGStqsLYIzs/ZJqStTsSUPymmFvxYYA/QGNgRuAK6rZlBm1n5JpVvg89IKX04CVUT8NSKWpOVqirziaWa2quqlH2ixd+G7pdX7JZ0GjCZLnIcBt7dBbGbWTuXlEb2UYo1Ik8gSZtM3ObZgXwA/rVZQZtZ+idXjXfhN2zIQM7Mmq0MJdDlJWwMDgM5N2yLiL9UKyszat/pIn2UkUEnnAAPJEugdwH7AQ4ATqJm1OonctLKXUk4r/CHA3sDrEXEUsC3QWNWozKxdq5d+oOU8wi+MiGWSlkhaF5gDuCO9mVVNTvJjSeWUQCdK+n/AlWQt848Dj1YzKDNrv4RoUOml5HWkzpIelfSkpMmSzkvbu0m6R9IL6WfXgnNOlzRN0lRJ+5a6Rznvwv8grV4uaTywbkQ8VTJ6M7NKtF5H+UXAXhHxnqQ1gIck3Ql8Hbg3Ii5IfdxPA/5L0gBgCLAV2VuXf5e0RUQ0O3xnsY70OxTbFxGPV/ad2sb2W/bhHw9fVOswrAW67nx8rUOwFlo07d9VuW5r1HFGRADvpY9rpCWAwWQN4wCjgAnAf6XtoyNiETBd0jRgF+Dh5u5RrAT662KxAXuV/AZmZi0koEN5CbS7pMLJL6+IiCs+di2pA1nV46eAyyLin5J6RcQsgIiYJalnOnwj4JGC02ekbc0q1pH+S+V8AzOz1lZmL6Z5EbFTsQPS4/d2qR3n5tSnvTkru2vRcT/KaUQyM2tTDSq9tEREvEX2qD4ImC2pN0D6OScdNgPoU3DaxsDMonG2LAwzs+rKRlta9X6gknqkkieS1gT2AZ4DxgHD0mHDgLFpfRwwRFKjpE2B/pTocVTWq5xmZm2plV5E6g2MSvWgDcCYiLhN0sPAGElHA68ChwJExGRJY4ApwBJgeLEWeCjvVU6RTemxWUScL6kvsEFEuC+omVVFa3RjSt0tt1/J9vlkb1eu7JwRwIhy71HOI/xIYDfg8PT5XeCycm9gZtYSAjpKJZc8KOcR/nMRsYOkfwFExJtpemMzs6rISX4sqZwEujjVIQRkFbPAsqpGZWbtlsp8VTMPynmE/x1wM9BT0giyoex+XtWozKxdq/s5kZpExDWSJpFVugo4OCKerXpkZtZu1clwoGW1wvcF3gduLdwWEa9WMzAza59E/QyoXE4d6O18NLlcZ2BTYCrZiCVmZq2rgjeNaqWcR/htCj+nUZqObeZwM7NVpjqZFanFbyJFxOOSdq5GMGZmq8W0xk0knVTwsQHYAZhbtYjMrN1bbRIosE7B+hKyOtGbqhOOmdlqMi986kDfJSJ+3EbxmFk7l01rXOsoylNsSo+OEbGk2NQeZmbVUC9vIhUrgT5KVt/5hKRxwA3AgqadEfG3KsdmZu3QatWIBHQD5pPNgdTUHzQAJ1Azq4o6KYAWTaA9Uwv8M3yUOJsUnSfEzKxyomE16AfaAehCBRMtmZlVSqweJdBZEXF+m0ViZgYg6FgnlaDFEmh9fAMzW62sLiXQlc4ZYmZWbXXfjSki3mjLQMzMmtRJ/vS0xmaWL6K8qTLywAnUzPJFq8m78GZmbU1ABydQM7PK1Ef6dAI1sxyqkwKoE6iZ5Y1cB2pmVol6aoWvlzjNrB2RVHIp4xp9JN0v6VlJkyWdmLZ3k3SPpBfSz64F55wuaZqkqZL2LXUPJ1AzyxdlbyKVWsqwBDg5Ij4D7AoMlzQAOA24NyL6A/emz6R9Q8imbB8EjEyzcjTLCdTMcqXpEb7UUkpEzIqIx9P6u8CzwEbAYGBUOmwUcHBaHwyMjohFETEdmAbsUuweTqBmljut8Qi/wvU2AbYH/gn0iohZkCVZoGc6bCPgtYLTZqRtzXIjkpnlTpnpsbukiQWfr4iIKz5xLakL2UzC/xkR7xRJvi0e+9gJ1Mxyp8wC5ryI2Kn4dbQGWfK8pmAet9mSekfELEm9gTlp+wygT8HpGwMzi13fj/BmlitNr3KWWkpeJytqXgU8GxEXFewaBwxL68OAsQXbh0hqlLQp0J9scs1muQRqZjkj1Dovc+4BHAk8LemJtO0M4AJgjKSjgVeBQwEiYrKkMcAUshb84RGxtNgNnEDNLHda40WkiHiI5qtTVzpgfESMAEaUew8nUDPLlawbk1/lNDNrOXkwETOzijmBmplVwAMqW6s49rvf4c47bqNHz55MeuIZAN544w2OPOIwXnnlZfr124SrrxtD165dS1zJqu2528/j3QWLWLpsGUuWLuPzQy9kmy024pIzh7D2mo28MnM+R505incXfMBOW/Xj0p8cDmQlrRGX38G4+5+q8TfIl1Zqha869wPNsSOHfZuxt43/2LZfXXgBA/fam2eefYGBe+3Nry68oEbR2YoGHfNbdh1yAZ8feiEAvz/7CM763Vh2/sbPGXf/k/xoWNbwO/nFmewx9EJ2HXIBg4eP5JKzDqdDB/9VLCSVXvLAv7Uc+/wX9qRbt24f23bbrWP55pFZH+BvHjmMW8fdUoPIrBz9+/XkoUnTALjvkec4eO/tAFj4wWKWLl0GQGOnNYgo+rZgu6Qy/ssDJ9A6M2f2bHr37g1A7969mTtnTokzrC1EBLeOPJ5/XHMq3/n6HgBMeXEWBw7cBoCvf3kHNu71UVXLzlv3Y9KNZzLxhjM4YcTo5QnVUjcmlV7yoGp1oJKWAk+ne0wHjoyIt9KoKM8CUwsOvygi/pLO2x54HBgUEXcVXO+9iOhSrXjNVsVeR13MrLlv06NrF267/Himvvw6x557Db8+9RBO/95+3P6/T/Ph4o9eannsmVfY8ZARfHrTXvzx/CO56x9TWPThkhp+gzzJTwmzlGqWQBdGxHYRsTXwBjC8YN+LaV/T8peCfYcDD6WftoKevXoxa9YsAGbNmkWPnj1LnGFtYdbctwGY++Z7jLvvKXbeahOef3k2B/3gMvYYeiFjxk9i+oy5nzhv6vTZLFj4IVt9asO2Djm/yih95qUE2laP8A9TYlw9WP7y/yHAt4GvSOpc5bjqzgEHfpWr/5qNBXv1X0dx4EGDaxyRrdW5E13Waly+vs9uWzL5xZn06Jo9MEnitO/ty5U3PgRAvw3XX95o1Ld3V7bYpBevzJxfm+BzKHuEb5UR6auu6t2Y0pD4e5ONitJk84KX+wF+GBEPkr38Pz0iXpQ0Adgf+BtlknQMcAxAn759VzHy2vvWNw/nwf+dwLx589h8k435ydnnccqpp/HNw7/BqD9dRZ8+fblm9A21DrPd67n+Olx/0fcA6NihA9ffOZF7/u9Zhh8+kGMP2xOAsfc9wV/GPgLA7ttvxilHfYXFS5aybFlw4s+vZ/5bC2oWfx7lIz2Wpmq1ABbUgW4CTAK+EhFLUx3obenRfsVzLgOeiIgrJX2VrN700LSvRXWgO+64U/zjnxNLH2i50XXn42sdgrXQoqljWPb+nFbNd5/ZZvv40y33lzxut091nVRqPNBqq3odKNAP6MTH60A/IZVU/wM4W9LLwCXAfpLWqWKMZpZD7saURMTbwAnAKWl06ObsAzwZEX0iYpOI6Ec2kvTB1Y7RzPLFHekLRMS/gCfJpgyFVAdasJxA1up+8wqn3gQckdbXkjSjYDmpLWI3s7ZXLwm0ao1IK9ZXRsRBBR/XLPMa48iG2Sci3OnfrB0Q9fMuvAcTMbN8yVEJsxQnUDPLnTrJn06gZpZDdZJBnUDNLGfy002pFCdQM8uVptGY6oETqJnljxOomVll/AhvZlYhd2MyM6tQneRPJ1AzyxllY6jWAydQM8sV4Ud4M7OK1Un+9KycZpZDKmMp5zLS/0iaI+mZgm3dJN0j6YX0s2vBvtMlTZM0VdK+pa7vBGpmudOKAyr/GRi0wrbTgHsjoj9wb/qMpAFkQ25ulc4ZmQZ6b5YTqJnlTmuNBxoRD5DNClxoMDAqrY/io0HbBwOjI2JRREwHpgG7FLu+E6iZ5U6ZCbS7pIkFyzFlXr5XRMwCSD+b5gbfCHit4LgZlJhN2I1IZpYrLRhQeV4rTyq3spsWnXXTJVAzy5cySp+r2M1ptqTeAOnnnLR9BtCn4LiNgZnFLuQEama500qN8M0ZBwxL68OAsQXbh0hqlLQp0B94tNiF/AhvZvnTSh1BJV0HDCSrL50BnANcAIyRdDTwKnAoQERMljQGmAIsAYZHxNJi13cCNbOcab0BlSPi8GZ27d3M8SOAEeVe3wnUzHLFAyqbma0KJ1Azs8p4QGUzswp5NCYzswrVSf50AjWznFn1jvJtxgnUzHIlG1C5PjKoE6iZ5U59pE8nUDPLoTopgDqBmln+uBuTmVml6iN/OoGaWb5IfpXTzKxifoQ3M6tUfeRPJ1Azy586yZ9OoGaWP+7GZGZWkdYbULnanEDNLFeyVzlrHUV5nEDNLHecQM3MKuRHeDOzSng4OzOzyrTCvO9txgnUzPKnTjKoE6iZ5U5DnTzDO4GaWe7UR/p0AjWzPKqTDOoEama5425MZmYVqKc3kRQRtY6hKiTNBV6pdRxV0B2YV+sgrEVW599Zv4jo0ZoXlDSe7M+slHkRMag1791Sq20CXV1JmhgRO9U6Diuff2err4ZaB2BmVq+cQM3MKuQEWn+uqHUA1mL+na2mXAdqZlYhl0DNzCrkBGpmViEn0DonaSdJ69c6DrP2yAm0jknaF7gS2KjWsVh5pHp5x8bK4QRapyQNAv4b+FFEPCWpq6R1ah2XlbQ+gCT/3VsN+JdYhyR9lqzk+dOImCCpD3AtsH1tI7PmKNMTeEXSVyNimZNo/fMvsM5I2gR4DXge6CFpW+B64I6IeKCWsVnzIjMHOAr4k6T9m5KopA61js8q4wRaRyRtCoyOiDeBY4CvAjcC4yLikoLj9pPUqgM8WOuIiDHA0cBoSQdExDIgACQdJOnAmgZoLeIEWl86AyGpU0S8SJZEpwBLJXUDkHQ4cCHg+tAckDRI0k8k7da0LSJuISuJjpZ0YCqJHgtcDjxXo1CtAh4PtA5I2gp4EZgNfBARH0pqiIiZkk4ERpIl0Q/I/mIeFhEv1TBk+8gXgeOAQZImA5cC0yPiptQi/2dJtwG7APtHxLQaxmot5ASac5LWAoaTlT5/AbwtqUNELAWIiJdT6eUvQE/gGxExpWYB24rGAZ8CfgicBgwBBkg6KSJulPQGWTXMXhHxZA3jtAr4XficS6WUAWQly88AmwEjgCVkDUlrAB8C75CVTv9do1AtkbQlsCgipqfP44ApEXGapCOAq4H7gBnAb4HJEfFhzQK2ijmB1oHU3WUAcBIwDLgTWECWPHsBawMHRsSMmgVpAEjaH/gJcGTT47ik/sD3gKnAGcB3gZnA7sCEpkRr9ccJNIck7Qn8GjgTeDkink9JtOkv4trA8NT4sAZARCyuWcAGLH8z7Fzg3Ii4S1IXshb2TmQNRAcC+zV1N5Ok8F/AuuZW+HzamOxxfQ/gKklDgW4RMZWswSiAayV1jojFTp61J2kbsieDM1Py3By4Bdg8dTsbQVYCXf6U4ORZ/5xAc0RS77Q6HngWmEP2yDcIuEjSCal1/cq0v2tNArXlCt5tfxm4GfhGetnhCuCu9JptQ0Q8BTwIfMkd51cfTqA5IekAYKyk3hHxBnAOsF1EPEhWstkHGCbpDuBzwIURMat2EVvSCSAi3gWGAl3IupzdEhG/TMlzmaTtyGbmHN/Ug8Lqn+tAcyANDHImMCIixkvqCPQge1z/O1k3phMj4h5JRwJ3R8Ts2kVsAJK+AnwfeBJ4KiL+JmltsvrODhFxRDruaLLGv29ExOs1C9hanRNojaU3iOYBX4+IW1Ld2U8i4tuSzgB+BgyNiOtqGqh9TPpH7zw+6n+7IdlTwQtpVKymuuq7yTrSHxcRz9QqXqsOd6SvsYh4Q9JBwE8lvQRcDNyRdv8O2IDskdCttjmR/tG7AxgcEbdK2piskWh94IWIeDeVOq8H/gDs7JcbVk8ugeZEKtHcAZwRERekbksiazBaFhHfrWmA9jGpzvpCYLeIeCfVTa8FPEE2Wtb/kP3+Gl1XvfpyAs0RSV8GLgE+FxFvp21rABu7s3X+SNqP7ClhPFm3sz8A3cg6yj8JnBQR79QuQqs2J9CcSX8pf0NWsnmjxuFYCZL2Iavn7N3UsJeeHrpFxLyaBmdV525MORMRdwKnAn/3iOX5FxF/Bw4A7pPUK21b5uTZPrgEmlOSukTEe7WOw8ojaTBZ392d0iDJ1g44gZq1Ev+j1/44gZqZVch1bGZmFXICNTOrkBOomVmFnEDNzCrkBNqOSVoq6QlJz0i6IU1gV+m1/izpkLT+R0kDihw7UNLuFdzjZUndy92+wjEtah2XdK6kU1oao7UvTqDt28KI2C4itiabmO64wp2VDvwbEd8tMXjGQLL5gMzqmhOoNXkQ+FQqHd4v6VrgaUkdJP1S0mOSnkpTKKPMpZKmSLqdbEg30r4JknZK64MkPS7pSUn3ptHajwN+lEq/X5DUQ9JN6R6PSdojnbu+pLsl/UvSH8gG5yhK0i2SJkmaLOmYFfb9OsVyr6Qeadvmksancx5UNqOmWVk8nJ2RBnDej2xQDIBdgK0jYnpKQm9HxM6SGoF/SLob2B74NLAN2cygU8hGICq8bg+y0aT2TNfqlobvuxx4LyJ+lY67Frg4Ih6S1Be4i2xwjnOAhyLi/DT60ccSYjO+k+6xJvCYpJsiYj7ZRHyPR8TJks5O1z6ebOqN49I4np8jG8dzrwr+GK0dcgJt39aU9ERafxC4iuzR+tGC0Z++Any2qX4TWI9sdtA9gevS9BQzJd23kuvvCjzQdK0ig6PsAwzQ8umFWDcNSrwn8PV07u2S3izjO50g6WtpvU+KdT6wjGx8TsjmZf+bslkzdwduKLh3Yxn3MAOcQNu7hRGxXeGGlEgWFG4CfhgRd61w3P5kI64XozKOgawqabeIWLiSWMp+VU7SQLJkvFtEvC9pAtC5mcMj3fetFf8MzMrlOlAr5S7g+2lcUiRtkeb9eQAYkupIewNfWsm5DwNflLRpOrdb2v4usE7BcXeTPU6TjtsurT5ANlFb0zB/pWYhXQ94MyXPLclKwE0agKZS9BFkVQPvANMlHZruIUnblriH2XJOoFbKH8nqNx+X9AzZoMEdyabwfQF4Gvg98L8rnhgRc8nqLf8m6Uk+eoS+FfhaUyMScAKwU2qkmsJHvQHOA/aU9DhZVcKrJWIdD3SU9BTwU+CRgn0LgK0kTSKr4zw/bR8KHJ3imwwMLuPPxAzwYCJmZhVzCdTMrEJOoGZmFXICNTOrkBOomVmFnEDNzCrkBGpmViEnUDOzCv1/REivA0carP0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "classifier.fit(X_train, y_train)\n",
    "pred = classifier.predict(X_test)\n",
    "score = metrics.accuracy_score(y_test, pred)\n",
    "print(\"accuracy:   %0.3f\" % score)\n",
    "cm = metrics.confusion_matrix(y_test, pred)\n",
    "plot_confusion_matrix(cm, classes=['FAKE', 'REAL'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "26b19ef0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8929384965831435"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.fit(X_train, y_train)\n",
    "pred = classifier.predict(X_test)\n",
    "score = metrics.accuracy_score(y_test, pred)\n",
    "score"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}