Gaussian-nb.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[GaussianNB] Accuracy: train = 0.9525310912594149, test = 0.6113445378151261\n"
     ]
    },
    {
     "data": {
      "text/plain": [
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "\n",
    "# Train a Guassian Naive Bayes classifier\n",
    "nb = GaussianNB()\n",
    "\n",
    "nb.fit(features_train, y_train)\n",
    "\n",
    "# Calculate the mean accuracy score on training and test sets\n",
    "print(\"[{}] Accuracy: train = {}, test = {}\".format(\n",
    "        nb.__class__.__name__,\n",
    "        nb.score(features_train, y_train),\n",
    "        nb.score(features_test, y_test)))\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7.6 64-bit",
   "language": "python",
   "name": "python37664bitf2b8979454eb492e8e911544bb13ab4b"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}