naive_bayes_sklearn.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c9350952",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.datasets import fetch_20newsgroups\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.metrics import ConfusionMatrixDisplay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5e416cfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = fetch_20newsgroups()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "68a81db0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['alt.atheism',\n",
       " 'comp.graphics',\n",
       " 'comp.os.ms-windows.misc',\n",
       " 'comp.sys.ibm.pc.hardware',\n",
       " 'comp.sys.mac.hardware',\n",
       " 'comp.windows.x',\n",
       " 'misc.forsale',\n",
       " 'rec.autos',\n",
       " 'rec.motorcycles',\n",
       " 'rec.sport.baseball',\n",
       " 'rec.sport.hockey',\n",
       " 'sci.crypt',\n",
       " 'sci.electronics',\n",
       " 'sci.med',\n",
       " 'sci.space',\n",
       " 'soc.religion.christian',\n",
       " 'talk.politics.guns',\n",
       " 'talk.politics.mideast',\n",
       " 'talk.politics.misc',\n",
       " 'talk.religion.misc']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.target_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0ffd04e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "categories = ['talk.religion.misc','soc.religion.christian','sci.space','comp.graphics']\n",
    "train = fetch_20newsgroups(subset='train',categories=categories)\n",
    "test = fetch_20newsgroups(subset='test',categories=categories)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1e4ba5c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "From: jsledd@ssdc.sas.upenn.edu (James Sledd)\n",
      "Subject: Re: Dreams and out of body incidents\n",
      "Organization: Social Science Computing\n",
      "Lines: 6\n",
      "\n",
      "In article <May.14.02.10.02.1993.25119@athos.rutgers.edu> alisonjw@spider.co.uk (Alison J Wyld) writes:\n",
      ">From: alisonjw@spider.co.uk (Alison J Wyld)\n",
      ">PS. Just to make it clear, I don't do ( and have never tried ) OOBEs.\n",
      ">    I tend to think they are off limits for Christians.\n",
      "\n",
      "WHY?\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(train.data[5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ba7284db",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = make_pipeline(TfidfVectorizer(), MultinomialNB())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "59ee2d34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('tfidfvectorizer', TfidfVectorizer()),\n",
       "                ('multinomialnb', MultinomialNB())])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(train.data,train.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2ada03b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ConfusionMatrixDisplay.from_estimator(model,test.data,test.target,display_labels=test.target_names,\n",
    "                                      xticks_rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "bae248b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_category(s,train=train,model=model):\n",
    "    pred = model.predict([s])\n",
    "    return train.target_names[pred[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "58a1b4c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'sci.space'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predict_category('low quality')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e2e49a77",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "33bf03e6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.9.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}