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Upgrade notebooks to TensorFlow 1.0.0

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This commit is contained in:
Aurélien Geron
2017-02-17 11:51:26 +01:00
parent 146fde1127
commit d8176ec2cb
43 changed files with 3615 additions and 7542 deletions
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233
05_support_vector_machines.ipynb
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@@ -2,7 +2,10 @@
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"**Chapter 5 – Support Vector Machines**\n",
"\n",
@@ -11,14 +14,20 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Setup"
]
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"First, let's make sure this notebook works well in both python 2 and 3, import a few common modules, ensure MatplotLib plots figures inline and prepare a function to save the figures:"
]
@@ -27,7 +36,9 @@
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
"collapsed": true,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -64,7 +75,10 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Large margin classification"
]
@@ -73,7 +87,9 @@
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -97,7 +113,9 @@
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -152,7 +170,10 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Sensitivity to feature scales"
]
@@ -161,7 +182,9 @@
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -198,7 +221,10 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Sensitivity to outliers"
]
@@ -207,7 +233,9 @@
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -258,7 +286,10 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Large margin *vs* margin violations"
]
@@ -267,7 +298,9 @@
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -303,7 +336,9 @@
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -329,7 +364,9 @@
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -358,7 +395,9 @@
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
"collapsed": true,
"deletable": true,
"editable": true
},
"source": [
"# Non-linear classification"
@@ -368,7 +407,9 @@
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -409,7 +450,9 @@
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -432,7 +475,9 @@
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -468,7 +513,9 @@
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -506,6 +553,8 @@
"execution_count": 13,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true,
"scrolled": true
},
"outputs": [],
@@ -574,7 +623,9 @@
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -588,7 +639,9 @@
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -604,6 +657,8 @@
"execution_count": 16,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true,
"scrolled": true
},
"outputs": [],
@@ -638,7 +693,10 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Regression\n"
]
@@ -647,7 +705,9 @@
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -679,7 +739,9 @@
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -718,7 +780,9 @@
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -739,7 +803,9 @@
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -757,7 +823,10 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Under the hood"
]
@@ -766,7 +835,9 @@
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": true
"collapsed": true,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -779,7 +850,9 @@
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -822,7 +895,10 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Small weight vector results in a large margin"
]
@@ -831,7 +907,9 @@
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -867,7 +945,9 @@
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -885,7 +965,10 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Hinge loss"
]
@@ -894,7 +977,9 @@
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -916,14 +1001,20 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Extra material"
]
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Training time"
]
@@ -932,7 +1023,9 @@
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -945,7 +1038,9 @@
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -968,16 +1063,21 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Identical linear classifiers"
]
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 28,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -1000,14 +1100,17 @@
"svm_clf.fit(X_scaled, y)\n",
"lin_clf.fit(X_scaled, y)\n",
"\n",
"print(\"SGDClassifier(alpha={}): \".format(sgd_clf1.alpha), sgd_clf.intercept_, sgd_clf.coef_)\n",
"print(\"SGDClassifier(alpha={}): \".format(sgd_clf.alpha), sgd_clf.intercept_, sgd_clf.coef_)\n",
"print(\"SVC: \", svm_clf.intercept_, svm_clf.coef_)\n",
"print(\"LinearSVC: \", lin_clf.intercept_, lin_clf.coef_)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Linear SVM classifier implementation using Batch Gradient Descent"
]
@@ -1016,7 +1119,9 @@
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -1029,7 +1134,9 @@
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -1096,7 +1203,9 @@
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -1108,7 +1217,9 @@
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -1119,7 +1230,9 @@
"cell_type": "code",
"execution_count": 33,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -1132,7 +1245,9 @@
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
@@ -1161,6 +1276,8 @@
"execution_count": 35,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true,
"scrolled": true
},
"outputs": [],
@@ -1192,14 +1309,20 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Exercise solutions"
]
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"**Coming soon**"
]
@@ -1208,7 +1331,9 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
"collapsed": true,
"deletable": true,
"editable": true
},
"outputs": [],
"source": []
@@ -1230,7 +1355,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.1"
"version": "3.5.2+"
},
"nav_menu": {},
"toc": {