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TingNieTingNie
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‎Collaborative_Filter.ipynb

+18-78
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@@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 50,
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"execution_count": 6,
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"metadata": {
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"collapsed": true
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},
@@ -11,14 +11,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"(1682L, 943L) (1682L, 943L)"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n[[5 4 0 0 4]\n [3 0 0 0 3]\n [4 0 0 0 0]\n [3 0 0 0 0]\n [3 0 0 0 0]]\nAverage rating for movie 1 (Toy Story): 4.520679 / 5\n"
14+
"(1682L, 943L) (1682L, 943L)\n[[5 4 0 0 4]\n [3 0 0 0 3]\n [4 0 0 0 0]\n [3 0 0 0 0]\n [3 0 0 0 0]]\nAverage rating for movie 1 (Toy Story): 3.878319 / 5\n"
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]
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}
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],
@@ -37,15 +30,15 @@
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"print Y.shape,R.shape\n",
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"print Y[0:5,0:5]\n",
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"print 'Average rating for movie 1 (Toy Story): %f / 5'\\\n",
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" %(np.mean(Y[0,R[0,:]]))\n",
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" %(np.mean(Y[0,R[0,:]==1]))\n",
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"\n",
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 51,
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
@@ -71,7 +64,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 52,
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
@@ -116,7 +109,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 53,
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"execution_count": 9,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -157,14 +150,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 44,
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[ 0.14401176 -6.22590369 10.0516782 0.14401176 -6.22590369\n 10.0516782 ]\n [ 4.45625126 2.03223863 7.35329766 4.45625126 2.03223863\n 7.35329766]\n [ 0.11515446 -9.74467008 -1.91337529 0.11515446 -9.74467008\n -1.91337529]\n [ 0.90141124 -1.28554704 1.55376368 0.90141124 -1.28554704\n 1.55376368]]\n[[ -0.12785057 -0.73651273 -1.21583757 -0.12785057 -0.73651273\n -1.21583757]\n [ -2.72597491 4.66380798 0.23347243 -2.72597491 4.66380798\n 0.23347243]\n [ -0.42229439 -0.40927681 -11.5753487 -0.42229439 -0.40927681\n -11.5753487 ]\n [ 3.61809669 12.26402186 7.18521682 3.61809669 12.26402186\n 7.18521682]\n [ 1.15495755 -1.53477221 -2.08059821 1.15495755 -1.53477221\n -2.08059821]]\nx max relative error: 4.429443e-10\ntheta max relative error: 4.670187e-10\n"
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"[[ 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"
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]
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}
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],
@@ -205,7 +198,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 54,
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"execution_count": 11,
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"metadata": {},
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"outputs": [
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{
@@ -237,7 +230,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 55,
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
@@ -273,7 +266,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 60,
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
@@ -325,14 +318,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 69,
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"execution_count": 15,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Warning: Maximum number of iterations has been exceeded.\n Current function value: 27769.265138\n Iterations: 100\n Function evaluations: 152\n Gradient evaluations: 152\n(1682L, 10L) (944L, 10L)\n(1682L, 944L)\n[ 3.89489124 3.56569854 3.25036093 ..., 1.99989186 2.99999858\n 3.00004241]\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:Prefontaine (1997) \n"
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"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"
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]
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}
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],
@@ -387,74 +380,21 @@
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"print score.shape\n",
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"print my_score[:5]\n",
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"sort_index = my_score.argsort()\n",
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"favorite = 3\n",
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"favorite = 10\n",
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"for i in xrange(favorite):\n",
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" print \"favorite %d score is %d,for:%s\" \\\n",
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" %(i+1,my_score[sort_index[-(i+1)]],movieList[sort_index[-(i+1)]])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 49,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Optimization terminated successfully.\n Current function value: 1.617021\n Iterations: 4\n Function evaluations: 8\n Gradient evaluations: 8\n[-1.80851064 -0.25531915]\n"
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]
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}
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],
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"source": [
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"#an example of optimize\n",
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"args = (2, 3, 7, 8, 9, 10) # parameter values\n",
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"def f(x, *args):\n",
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" \n",
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" u, v = x\n",
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" a, b, c, d, e, f = args\n",
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" return a*u**2 + b*u*v + c*v**2 + d*u + e*v + f\n",
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"def gradf(x, *args):\n",
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" u, v = x\n",
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" a, b, c, d, e, f = args\n",
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" gu = 2*a*u + b*v + d # u-component of the gradient\n",
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" gv = b*u + 2*c*v + e # v-component of the gradient\n",
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" return np.asarray((gu, gv))\n",
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"x0 = np.asarray((0, 0)) # Initial guess.\n",
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"from scipy import optimize\n",
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"res1 = optimize.fmin_cg(f, x0, fprime=gradf, args=args)\n",
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"print res1"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 70,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[0 3 2 4 1 5]\nfavorite 1 score is 6,for f\nfavorite 2 score is 5,for b\nfavorite 3 score is 4,for e\n"
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]
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}
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],
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"source": [
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"y = np.array([1,5,3,2,4,6])\n",
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"yy = ['a','b','c','d','e','f']\n",
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"index = np.argsort(y)\n",
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"print index\n",
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"for i in xrange(3):\n",
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" print \"favorite %d score is %d,for %s\" \\\n",
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" %(i+1,y[index[-(i+1)]],yy[index[-(i+1)]])\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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"source": [
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"\n",
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"\n"
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]
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}
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],
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"metadata": {

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