{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 126.84247142  125.01176842]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn import linear_model\n",
    "import matplotlib.pyplot as plt \n",
    "\n",
    "X = [[0.44, 0.68], [0.99, 0.23]]\n",
    "vector = [109.85, 155.72]\n",
    "predict= [[0.49, 0.18], [0.47, 0.22]]\n",
    "\n",
    "poly = PolynomialFeatures(degree=2)\n",
    "X_ = poly.fit_transform(X)\n",
    "predict_ = poly.fit_transform(predict)\n",
    "\n",
    "clf = linear_model.LinearRegression()\n",
    "clf.fit(X_, vector)\n",
    "y=clf.predict(predict_)\n",
    "print (clf.predict(predict_))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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