bayesian_linear_regression.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# bayesian linear regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABECAYAAAAiJuZQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nPQpWNmHZBnMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x103f42fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from edward.models import Normal\n",
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "import edward as ed\n",
    "import seaborn as sns\n",
    "import matplotlib\n",
    "import matplotlib.cm as cm\n",
    "from matplotlib.colors import ListedColormap, Normalize\n",
    "from matplotlib.animation import FuncAnimation\n",
    "\n",
    "matplotlib.interactive(True)\n",
    "plt.style.use('seaborn-talk')\n",
    "\n",
    "sns.palplot(sns.color_palette())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sess = ed.get_session()\n",
    "ed.set_seed(42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1143e0e10>]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ZVLczbzHuDI/F0dhXpCFz9mAP1+ua4vrsTp+XG32tgOrpJuIyUlgxfMqGjgyT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\nijohhBBCiCjw/wGaecJC+AUg1QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f1e7860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x= tf.range(-5.0,5.0,0.001)\n",
    "plt.plot(*sess.run([x, Normal(loc=tf.ones(1) * 0.0,\n",
    "                            scale =tf.ones(1)*1.0).prob(x)]))\n",
    "plt.plot(*sess.run([x, Normal(loc=tf.ones(1)*2.0,\n",
    "                             scale=tf.ones(1)*1.0).prob(x)]))\n",
    "plt.plot(*sess.run([x, Normal(loc=tf.ones(1)*0.0,\n",
    "                             scale=tf.ones(1)*1.0).prob(x)]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# data\n",
    "N1 = 10 # number of training data points in first batch \n",
    "N2 = 90 # number of training data points in second batch\n",
    "Np = 10 # number of test data points\n",
    "D = 1 # number of features\n",
    "\n",
    "weights_true = sess.run(Normal(loc=tf.ones(D) * 2.0,\n",
    "                              scale=tf.ones(D) * 0.1)) # unknown true weights\n",
    "intercept_true = sess.run(Normal(loc=tf.zeros(1),\n",
    "                                scale=tf.ones(1)))\n",
    "noise_true = 0.35 # unknown true amount of noise\n",
    "\n",
    "def build_dataset(N):\n",
    "    x = Normal(loc=tf.zeros([N,D]), scale=tf.ones([N,D]))\n",
    "    y = Normal(loc=ed.dot(x,weights_true) + intercept_true, scale=noise_true)\n",
    "    return sess.run([x,y])\n",
    "\n",
    "x_train1, y_train1 = build_dataset(N1)\n",
    "x_train2, y_train2 = build_dataset(N2)\n",
    "x_test, y_test = build_dataset(Np)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x115e9dfd0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AkDiFDQAgcQobAEDifOgA4A2cyrchAIwkO2wAb8C3IQCpsMMGE0R3W1scbNocPa2tUVVX\nFzNXN0Z1oVDusZLm2xCAVNhhgwniYNPm6NizO7peOBAde3bHwabN5R4peb4NAUiFwgYTRE9r66DH\nDOTbEIBUeEkUJoiqurroeuFAv2MG59sQgFTYYYMJYubqxph27vyYPGt2TDt3fsxc3VjukQAYJjts\nMEFUFwox+6abyz1GElyuAxhr7LABE47LdQBjjR02ICndbW3x4uavjOjlR1yuAxhr7LABSfnvr478\n5UdcrgMYaxQ2ICmjcfkRl+sAxhoviQJJqaqri84Dz/c7LjWX6wDGGjtsQFJ+4f+4/AjA69lhA5Li\n8iMAA9lhAwBInMIGAJC4khW2O++8Mz772c+W6uEAAPiZogtba2trfPrTn46HHnqoFPMAAPA6RX/o\nYNWqVbFw4cK4/PLLSzEPQFn4flEgZUMWtp6enujo6Bhwe2VlZdTW1kZTU1PMnDkzPv3pT5/yk1dU\nVETlCL+LrrKyot9Phkdu+cgtv3Jn1/TdH8TufS0REXHg5fZoeuIHcfM16V+rrdy5jVVyy0du+ZQi\ntyEL286dO6OhoWHA7bNmzYrt27fHzJkzcz/5jBk1UVExOr/0QqFmVJ5nvJFbPnLLr1zZHe7oGnBc\nX19bllnysObykVs+csunmNyGLGwXXXRRPPfcc7mfYDDNze2jssNWKNREW1t79PVlI/tk44jc8pFb\nfuXO7vRpkwcct7QcHfU5TlW5cxur5JaP3PIZKrfh/MdhWS+cm2VZ9PaOznP19WXR22txnSq55SO3\n/MqV3eoPnBNbHv/f97Ct/sA5Y+p3aM3lI7d85JZPMbn5pgOA8P2iQNoUNqBsutva4mDT5uhpbY3q\n+vqo+eSNEVFd7rEAklOywrZhw4ZSPRQwQRxs2hwde3ZHRETXCwfiR1/aGL/wezeVeSqA9PhqKqBs\nelpb+x13tTSXaRKAtClsQNlU1dX1O55cP6NMkwCkTWEDymbm6saYdu78mDxrdtTMf2e89ff+b7lH\nAkiSDx0AZVNdKMTsm26OiIhJkypiSn1ttI+Ba58BjDY7bAAAiVPYAAASp7ABACROYQMASJzCBgCQ\nOIUNACBxChsAQOIUNgCAxClsAACJU9gAABKnsAEAJE5hAwBInMIGAJA4hQ0AIHEKGwBA4hQ2AIDE\nVZV7AGDiaDvSGVue2ButRzqjbvqUaFg2Lwq1U8o9FkDy7LABo2bLE3tj976WOPBye+ze1xJbHt9b\n7pEAxgSFDRg1rUc6Bz0G4OQUNmDU1E2fMugxACensAGjpmHZvJg/pz5mn1ET8+fUR8OyeeUeCWBM\n8KEDYNQUaqfEJz60oNxjAIw5dtgAABKnsAEAJE5hAwBInMIGAJA4hQ0AIHEKGwBA4hQ2AIDEKWwA\nAIlT2AAAEqewAQAkTmEDAEicwgYAkDiFDQAgcQobAEDiFDYAgMQpbAAAiSu6sG3atCkuueSSWLx4\ncVx77bXxwx/+sBRzAQDwM0UVtm9/+9uxbdu2eOihh+LJJ5+MJUuWxNq1a6Ovr69U8wEATHhFFbbW\n1tZYt25dnHXWWVFVVRUf/ehH48UXX4yXXnqpVPMBAEx4VUOd0NPTEx0dHQNur6ysjMbGxn63bd++\nPQqFQrzlLW8p3YQAABPckIVt586d0dDQMOD2WbNmxfbt2/udd9ttt8Udd9wRlZXD27irqKiIYZ6a\nW2VlRb+fDI/c8pFbfrLLR275yC0fueVTitwqsizLih3k0Ucfjc985jOxfv36uPrqq4d9vyzLoqLC\nLx0AYDBD7rANZePGjfHggw/Gpk2bYsmSJad03+bm9lHZYSsUaqKtrT36+oruphOG3PKRW36yy0du\n+cgtH7nlM1Ru9fW1Qz5GUYXtkUceiQceeCC+/vWvx9y5c0/5/lmWRW9vMRMMX19fFr29Ftepkls+\ncstPdvnILR+55SO3fIrJrajCdv/990d7e3usXLmy3+1bt27NVeAAABioqML2t3/7t6WaAwCAN+Cr\nqQAAEqewAQAkTmEDAEicwgYAkDiFDQAgcQobAEDiFDYAgMQpbAAAiVPYAAASp7ABACROYQMASJzC\nBgCQOIUNACBxChsAQOIUNgCAxClsAACJU9gAABKnsAEAJE5hAwBInMIGAJA4hQ0AIHEKGwBA4hQ2\nAIDEKWwAAIlT2AAAEqewAQAkTmEDAEicwgYAkDiFDQAgcQobAEDiFDYAgMQpbAAAiVPYAAASp7AB\nACROYQMASJzCBgCQOIUNACBxChsAQOIUNgCAxClsAACJU9gAABKnsAEAJE5hAwBIXFGFraurK26/\n/fa48MILY9GiRfGxj30sDh48WKrZAACIIgvbxo0b48c//nF897vfjX/7t3+LQqEQf/Inf1Kq2QAA\niIiqYu584403Rnd3d0ydOjVaW1ujvb096urqSjUbAAAxjMLW09MTHR0dA26vrKyM2tramDRpUnz5\ny1+OL3/5y3HmmWfG1772tREZFABgohqysO3cuTMaGhoG3D5r1qzYvn17RERcd911sWbNmvizP/uz\naGxsjMceeyyqq6uHfPKKioqoHOGPPVRWVvT7yfDILR+55Se7fOSWj9zykVs+pcitIsuyrFQDdXV1\nxcKFC+Ob3/xmvOMd7xjy/CzLoqLCLx0AYDBFvYftj/7oj2L+/PmxatWqiIjo7e2Nvr6+OP3004d1\n/+bm9lHZYSsUaqKtrT36+krWTcc9ueUjt/xkl4/c8pFbPnLLZ6jc6utrh3yMogrbO9/5zti8eXNc\nfPHFMWPGjLjrrrti0aJFcdZZZw3r/lmWRW9vMRMMX19fFr29Ftepkls+cstPdvnILR+55SO3fIrJ\nrajCds0110Rzc3N85CMfie7u7nj3u98dX/ziF4t5SAAAXqeowlZRUREf//jH4+Mf/3ip5gEA4HV8\nNRUAQOIUNgCAxClsAACJU9gAABKnsAEAJE5hAwBInMIGAJA4hQ0AIHEKGwBA4hQ2AIDEKWwAAIlT\n2AAAEqewAQAkTmEDAEicwgYAkDiFDQAgcQobAEDiFDYAgMQpbAAAiVPYAAASp7ABACROYQMASJzC\nBgCQOIUNACBxChsAQOIUNgCAxClsAACJU9gAABKnsAEAJE5hAwBInMIGAJA4hQ0AIHEKGwBA4hQ2\nAIDEKWwAAIlT2AAAEqewAQAkTmEDAEhcVbkHGGltRzrjnkd2x/80d0Rh+uRoWDYvCrVTyj0WAMCw\njfsdts2P7Y3/94P/iedfPhq797XElsf3lnskAIBTMu4LW+vhzv7HRzrf4EwAgDSN+8JWd3r/lz/r\npns5FAAYW8Z9YWtcPi8WnXNmnHVGbcyfUx8Ny+aVeyQAgFNSsg8dbN26NT73uc/FU089VaqHLIlC\n7ZS4/bol0dJyNHp7s3KPAwBwykqyw/b888/Hhg0bSvFQAAC8TtGFrbe3N/7wD/8wPvzhD5diHgAA\nXmfIwtbT0xOHDx8e8Ofo0aMREXH//ffHr/7qr8bFF1884sMCAExEQ76HbefOndHQ0DDg9lmzZsU9\n99wT3/nOd2Lr1q2xZ8+eU37yioqKqBzhjz1UVlb0+8nwyC0fueUnu3zklo/c8pFbPqXIbcjCdtFF\nF8Vzzz034Pbjx4/HypUr484774yamppcTz5jRk1UVIzOL71QyDfjRCe3fOSWn+zykVs+cstHbvkU\nk1tFlmW5Pjq5a9euaGxsjOrq6oh49b1sx44di9ra2vjOd74Tv/iLvzjkYxw6dHRUdtgKhZpoa2uP\nvj6fEh0uueUjt/xkl4/c8pFbPnLLZ6jc6utrh3yM3Jf1WLx4cfzHf/zHieOnnnoqbrzxxlO6rEeW\nZdHbm3eCU9PXl7msRw5yy0du+ckuH7nlI7d85JZPMbmN+wvnAgCMdSUrbBdccEFyF80FABgP7LAB\nACROYQMASJzCBgCQOIUNACBxChsAQOJyXzgXAIDRYYcNACBxChsAQOIUNgCAxClsAACJU9gAABKn\nsAEAJE5hAwBInMIGAJC4cVnYNm3aFJdcckksXrw4rr322vjhD3940vO6urri1ltvjfPPPz8uuuii\nuPfee0d50jTdeeed8dnPfvYN/76lpSV+7dd+Lc4777wTf/74j/94FCdM01C5WW8DNTU1xXve855Y\nuHBhfOpTn4qOjo6TnjfR19yzzz4bK1eujAULFsSKFSvi6aefPul5f/M3fxPvf//7Y8GCBbF27do4\ndOjQKE+anuFmt3bt2njnO9/Zb40R8cwzz8TSpUvf8O+tuZMbKrdc6y0bZx555JHssssuy376059m\n3d3d2caNG7NLLrkk6+3tHXDuhg0bst/93d/NDh8+nO3fvz973/velz322GNlmDoNLS0t2S233JK9\n7W1vyzZs2PCG5/3zP/9zdsUVV4ziZGkbbm7WW3/bt2/Pli5dmu3bty87fPhwtmbNmuy222476bkT\nec0dP348e8973pN97Wtfy7q6urJvfetb2YUXXpgdPXq033l79+7NFi5cmD399NPZsWPHsltvvTVb\ns2ZNmaZOw3Czy7IsW7p0afbMM8+UYco09fX1Zd/61reyRYsWZeeff/5Jz7HmBhpOblmWb72Nux22\n1tbWWLduXZx11llRVVUVH/3oR+PFF1+Ml156acC527Zti7Vr18b06dPjV37lV+J3fud34q/+6q/K\nMHUaVq1aFZMmTYrLL7980POeffbZOOecc0ZpqvQNNzfrrb9t27bFypUr4+yzz47p06fH7//+78e2\nbduit7d3wLkTec09+eSTUVlZGatWrYrq6upYuXJlvPnNb44dO3b0O++v//qv4/3vf3+8613viqlT\np8anPvWp+Kd/+qcJveMx3Oyam5ujpaUl3va2t5Vp0vTcd9998eCDD8a6deve8BxrbqDh5JZ3vY3J\nwtbT0xOHDx8e8Ofo0aPR2NgYv/mbv3ni3O3bt0ehUIi3vOUt/R7jlVdeiebm5njrW9964razzz47\n9u3bN2r/HKNtsNwiXn156q677opp06YN+jh79+6Nn/70p/Ebv/EbsXTp0rj11lvj8OHDo/GPUBal\nyG0irreIwbPbt2/fgDw6Ojri4MGDAx5noq2519q/f3/MnTu3320nWzuvz7Ouri7e9KY3xf79+0dl\nzhQNN7tnn302ampqYu3atXHhhRfGNddcE9///vdHc9TkfPCDH4xt27bF/Pnz3/Aca26g4eSWd71V\nlXLQ0bJz585oaGgYcPusWbNi+/bt/c677bbb4o477ojKyv7d9NixYxERcdppp524berUqXH8+PER\nmrr8hspt5syZw3qc2trauOCCC2LNmjXR3d0dt9xyS9x2223xhS98odQjJ6EUuU3E9RYxeHaTJk2K\nqVOnnrjt59n8PKvXmmhr7rU6Ojr6rZuIk6+dY8eO9csz4tVMT5bnRDHc7Do7O2PBggXxB3/wB/HL\nv/zLsXXr1rjuuuviiSeeiDPOOGM0R07GmWeeOeQ51txAw8kt73obk4Xtoosuiueee27Qcx599NH4\nzGc+E+vXr48rr7xywN//fJEdP348amtrT/zvoXaXxrLh5DYcd9xxR7/jT3ziE/Hbv/3b0dfXN6AY\njwelyG0irreIwbO78soro7Oz88Txz/8lX1NTM+DcibbmXuu0004bUDBOtnbeqMSN9zU2mOFmd+ml\nl8all1564njVqlXx9a9/PZ566qlYvnz5qMw6Fllz+eRdb+Py33QbN26MP/3TP41NmzbF1VdffdJz\nCoVCzJgxo9/W7cm2z+mvr68vPv/5z8eBAwdO3NbZ2RnV1dXj/v84i2G9DTR37tx+L03t378/Tj/9\n9AH/hTrR19ycOXMGvMS0f//+fi9FRbya52vPa2lpiVdeeWVCr7HhZvfd7343Hn/88X63dXZ2xpQp\nU0Z8xrHMmssn73obd/+2e+SRR+KBBx6Iv/zLv4wlS5YMeu5VV10VX/rSl6KtrS1+8pOfxMMPPxwr\nVqwYpUnHpsrKynj66afj7rvvjo6Ojnj55Zfj7rvv7ve+QU7Oeuvvqquuim9+85vxX//1X3H06NG4\n5557Yvny5QNK2ERfc0uWLImurq546KGHoru7O7Zu3RqHDh0acMmA5cuXx9/93d/Frl27orOzM+6+\n++64+OIimPo/AAABZ0lEQVSLo66urkyTl99ws+vo6Ii77rorfvSjH0V3d3d85StfiePHj8e73/3u\nMk0+Nlhz+eReb8V+hDU1l112Wfb2t789W7BgQb8/P/rRj7Isy7IFCxZk3/ve97Isy7Jjx45l69ev\nzy688MJsyZIl2b333lvO0ZNxyy23DLg8xWtze+mll7Ibbrgh+/Vf//Xs/PPPz26//fass7OzHKMm\nZajcrLeBHnjggex973tftmjRouyTn/xk1tHRceLvrLn/tXfv3uzDH/5wtmDBgmzFihXZ97///SzL\nsmz9+vXZ+vXrT5z32GOPZZdddll23nnnZdddd1126NChco2cjOFmd99992Xvfe97s3e9613ZRz7y\nkewHP/hBuUZOypNPPtnv8hTW3PAMlVue9VaRZVk2Op0SAIA8xt1LogAA443CBgCQOIUNACBxChsA\nQOIUNgCAxClsAACJU9gAABKnsAEAJE5hAwBI3P8H5DHrPbqdSPMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114915160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x_train1, y_train1, s=20.0)\n",
    "plt.scatter(x_test, y_test,s=20.0,color=sns.color_palette().as_hex()[2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Little noise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from edward.models import Empirical, Normal\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Forward model\n",
    "x = tf.placeholder(tf.float32,[N1,D])\n",
    "weights = Normal(loc=tf.zeros(D),scale=tf.ones(D))\n",
    "intercept = Normal(loc=tf.zeros(1), scale=tf.ones(1))\n",
    "y = Normal(loc=ed.dot(x,weights)+ intercept,\n",
    "          scale=tf.ones(N1) ) # with more noise "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# BACKWARD MODEL\n",
    "T = 10000\n",
    "q_weights = Empirical(params=tf.Variable(tf.zeros([T,D])))\n",
    "q_intercept = Empirical(params=tf.Variable(tf.zeros([T,1])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000/10000 [100%] ██████████████████████████████ Elapsed: 99s | Acceptance Rate: 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     ]
    }
   ],
   "source": [
    "# inference \n",
    "inference = ed.HMC(latent_vars={weights: q_weights,\n",
    "                                intercept: q_intercept},\n",
    "                   data={x: x_train1,\n",
    "                         y: y_train1})\n",
    "inference.run(step_size=0.01 / N1, n_steps=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[<matplotlib.lines.Line2D at 0x1256f4d30>],\n",
       " [<matplotlib.lines.Line2D at 0x1240873c8>],\n",
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       " [<matplotlib.lines.Line2D at 0x12087fe80>],\n",
       " [<matplotlib.lines.Line2D at 0x1208b9cf8>]]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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nuq+EZVmqrDhd1zEMA9u2uy7YD4WIOEEQBEH4nvCm+1ZVFVVVPnDfwjDC933K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Y2iiLiPyWTKfL43jEZtDg72uHnzFW7cOOYrX7lDFBUURcl6vf7Ygbvicrb8QLdNuHVixPq8eiyJ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x123fca2b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# criticism\n",
    "plt.scatter(x_train1, y_train1, s=20.0)\n",
    "plt.scatter(x_test, y_test, s=20.0, color = sns.color_palette().as_hex()[2])\n",
    "\n",
    "xp = tf.placeholder(tf.float32, [2,D])\n",
    "[plt.plot(np.linspace(-4.0,4.0,2),\n",
    "         sess.run(ed.dot(xp, q_weights.params[t]) + q_intercept.params[t],\n",
    "                 {xp:np.linspace(-4.0,4.0,2)[:,np.newaxis]}),\n",
    "         color='k',alpha=0.1)\n",
    "for t in range(int(T/2),T,int(T/100))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_post = ed.copy(y, {weights: q_weights, \n",
    "                    intercept: q_intercept})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean squared error on test data:\n",
      "0.111212\n",
      "mean absolute error on test data\n",
      "0.338317\n"
     ]
    }
   ],
   "source": [
    "print('Mean squared error on test data:')\n",
    "print(ed.evaluate('mean_squared_error', data ={x: x_test, y_post: y_test}))\n",
    "\n",
    "print(\"mean absolute error on test data\")\n",
    "print(ed.evaluate('mean_absolute_error', data={x: x_test, y_post: y_test}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# prior on noise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from edward.models import InverseGamma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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