{
 "cells": [
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "import spacy\n",
    "from notebook_functions import *\n",
    "\n",
    "def extract_all_features(sentence_pairs):\n",
    "    features = []\n",
    "    for sent1, sent2 in sentence_pairs:\n",
    "        feature_vector = [\n",
    "            jaccard_similarity(sent1, sent2),\n",
    "            sentence_similarity_avg(sent1, sent2),\n",
    "            sentence_similarity_sif(sent1, sent2),\n",
    "            syntactic_similarity(sent1, sent2)\n",
    "        ]"
   ],
   "id": "1c45d83192facfc6"
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "labled_pairs = []\n",
    "\n",
    "X = extract_all_features(labled_pairs)\n",
    "y = [0,1,0,1...] #Lables for pairs\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n",
    "model = LogisticRegression()\n",
    "model.fit(X_train, y_train)\n"
   ],
   "id": "9665682bd5a7951e"
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 5
}