Skip to content

Commit

Permalink
updated the look and feel of the pages
Browse files Browse the repository at this point in the history
  • Loading branch information
zreyn committed Nov 22, 2016
1 parent f330452 commit 8c084d6
Show file tree
Hide file tree
Showing 3 changed files with 54 additions and 65 deletions.
49 changes: 20 additions & 29 deletions notebooks/nfl-modeling.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -322,7 +322,22 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# gradient boosting classifier\n",
"gbc = GradientBoostingClassifier(learning_rate=0.1, n_estimators=100, \n",
" subsample=1.0, min_samples_leaf=20, max_depth=3, random_state=22,\n",
" max_features=1.0)\n",
"gbc.fit(X, y)"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {
"collapsed": false
},
Expand All @@ -331,46 +346,22 @@
"name": "stdout",
"output_type": "stream",
"text": [
"[ 0.75736464 0.75149487 0.75249616]\n"
"0.754077734808\n"
]
}
],
"source": [
"# gradient boosting classifier\n",
"gbc = GradientBoostingClassifier(subsample=0.5)\n",
"gbc.fit(X, y)\n",
"print(cross_val_score(gbc, X, y)) "
"print sum(cross_val_score(gbc, X, y, cv=10))/10."
]
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": null,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.761128939357\n",
"[[1143 8 10]\n",
" [ 20 5465 1322]\n",
" [ 10 1533 2642]]\n"
]
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAFNCAYAAAAO36SFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nzinQi4jknAK9iEjO/X9ImST6Yi3pSQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1161ef8d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"outputs": [],
"source": [
"y_pred = gbc.predict(X_test)\n",
"print gbc.score(X_test, y_test)\n",
Expand Down
Loading

0 comments on commit 8c084d6

Please sign in to comment.