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Author: TingNie

Collaborative_Filter.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 2,
    "metadata": {
     "collapsed": true
    },
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -65,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -111,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -152,14 +152,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 3.2694473   0.82260885  0.34742436  3.2694473   0.82260885  0.34742436]\n [ 0.60548622 -5.29818853 -8.71667995  0.60548622 -5.29818853 -8.71667995]\n [ 0.98872539 -5.60773103 -7.1520766   0.98872539 -5.60773103 -7.1520766 ]\n [ 1.27425229  5.80646836 -0.94849499  1.27425229  5.80646836 -0.94849499]]\n[[ -3.21431313  -0.73938093  -0.17662467  -3.21431313  -0.73938093\n   -0.17662467]\n [  1.62875238  -7.84411116 -10.54935153   1.62875238  -7.84411116\n  -10.54935153]\n [  1.04497469   0.56498113   1.51627789   1.04497469   0.56498113\n    1.51627789]\n [  0.57523149  -0.36704409   0.23436928   0.57523149  -0.36704409\n    0.23436928]\n [ -1.08518528  -3.44655202  -0.38480487  -1.08518528  -3.44655202\n   -0.38480487]]\nx max relative error: 5.289068e-10\ntheta max relative error: 2.211348e-10\n"
+      "[[ -1.4485962   -2.38226893   1.70710777  -1.4485962   -2.38226893\n    1.70710777]\n [ -2.18041855   6.88240991  -7.8848515   -2.18041855   6.88240991\n   -7.8848515 ]\n [  8.23023857  -1.02191424  -4.0025453    8.23023857  -1.02191424\n   -4.0025453 ]\n [ 14.13447555  -5.85369614  -5.0379881   14.13447555  -5.85369614\n   -5.0379881 ]]\n[[  0.73826162   2.09184519  -0.48151182   0.73826162   2.09184519\n   -0.48151182]\n [  1.18589767   1.21853183  -1.81195221   1.18589767   1.21853183\n   -1.81195221]\n [ -5.30305981   8.71447069 -11.02419571  -5.30305981   8.71447069\n  -11.02419571]\n [ 10.43018863  -4.31754416  -6.23177659  10.43018863  -4.31754416\n   -6.23177659]\n [  0.27896481  -1.40228679   1.58240075   0.27896481  -1.40228679\n    1.58240075]]\nx max relative error: 6.712613e-11\ntheta max relative error: 1.661263e-10\n"
      ]
     }
    ],
@@ -200,7 +200,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -232,7 +232,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -268,7 +268,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -308,26 +308,19 @@
     "XX = np.random.randn(num_movies1,num_features1)\n",
     "TTheta = np.random.randn(num_users1,num_features1)\n",
     "print XX.shape\n",
-    "print TTheta.shape\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n"
+    "print TTheta.shape"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Warning: Maximum number of iterations has been exceeded.\n         Current function value: 27848.964019\n         Iterations: 100\n         Function evaluations: 149\n         Gradient evaluations: 149\n(1682L, 10L) (944L, 10L)\n(1682L, 944L)\n[ 4.13867803  3.96850127  4.31376906  3.68773897  3.73023817]\nfavorite 1 score is 5,for:Princess Bride, The (1987) \nfavorite 2 score is 5,for:Star Wars (1977) \nfavorite 3 score is 5,for:Affair to Remember, An (1957) \nfavorite 4 score is 5,for:Entertaining Angels: The Dorothy Day Story (1996) \nfavorite 5 score is 5,for:Great Day in Harlem, A (1994) \nfavorite 6 score is 5,for:Prefontaine (1997) \nfavorite 7 score is 5,for:They Made Me a Criminal (1939) \nfavorite 8 score is 5,for:Santa with Muscles (1996) \nfavorite 9 score is 5,for:Aiqing wansui (1994) \nfavorite 10 score is 5,for:Saint of Fort Washington, The (1993) \n"
+      "Warning: Maximum number of iterations has been exceeded.\n         Current function value: 27696.300753\n         Iterations: 100\n         Function evaluations: 149\n         Gradient evaluations: 149\n"
      ]
     }
    ],
@@ -366,7 +359,23 @@
     "    return g\n",
     "\n",
     "    \n",
-    "res = optimize.fmin_cg(Cost,x0=params,fprime=grad,args=args,maxiter=100)\n",
+    "res = optimize.fmin_cg(Cost,x0=params,fprime=grad,args=args,maxiter=100)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(1682L, 10L) (944L, 10L)\n(1682L, 944L)\n[ 3.83399475  3.34586129  4.46180229  3.76026786  3.44922026]\nfavorite 1 score is 5,for:Return of the Jedi (1983) \nfavorite 2 score is 5,for:Star Wars (1977) \nfavorite 3 score is 5,for:Empire Strikes Back, The (1980) \nfavorite 4 score is 5,for:Independence Day (ID4) (1996) \nfavorite 5 score is 5,for:Renaissance Man (1994) \nfavorite 6 score is 5,for:Star Kid (1997) \nfavorite 7 score is 5,for:Marlene Dietrich: Shadow and Light (1996) \nfavorite 8 score is 5,for:Saint of Fort Washington, The (1993) \nfavorite 9 score is 5,for:Santa with Muscles (1996) \nfavorite 10 score is 5,for:Someone Else's America (1995) \n"
+     ]
+    }
+   ],
+   "source": [
     "#get the bestX,bestTheta\n",
     "#改变一下参数的shape\n",
     "bestX = res[0:num_movies1*num_features1].reshape(num_movies1,num_features1)\n",
@@ -385,18 +394,17 @@
     "favorite = 10\n",
     "for i in xrange(favorite):\n",
     "    print \"favorite %d score is %d,for:%s\" \\\n",
-    "          %(i+1,my_score[sort_index[-(i+1)]],movieList[sort_index[-(i+1)]])"
+    "          %(i+1,my_score[sort_index[-(i+1)]],movieList[sort_index[-(i+1)]])\n",
+    "    \n",
+    "\n"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "\n",
-    "\n"
-   ]
+   "source": []
   }
  ],
  "metadata": {