【申精】花花公子成人频道Playboy TV-Spring Break (春假派对系列 全）

rogercheng

尝试下西片吧

gu80542

偶尔换个口味

功夫茶

import numpy as np
& ~/ p7 a2 ^7 h% q1 Aimport matplotlib.pyplot as plt
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import utilities
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# Load input data
input_file = 'D:\\1.Modeling material\\Py_Study\\2.code_model\\Python-Machine-Learning-Cookbook\\Python-Machine-Learning-Cookbook-master\\Chapter03\\data_multivar.txt'
X, y = utilities.load_data(input_file)
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1 D7 S; v, D! _& T###############################################
3 \! G( A! r- b2 i) U# Separate the data into classes based on 'y'
class_0 = np.array([X[i] for i in range(len(X)) if y[i]==0])
class_1 = np.array([X[i] for i in range(len(X)) if y[i]==1])

3 a# {3 J4 l, g& t5 J# g) P# Plot the input data
: Z% I5 T' B% U5 i& ?plt.figure()
, `1 B/ j% P" k: _& E9 F& ^plt.scatter(class_0[:,0], class_0[:,1], facecolors='black', edgecolors='black', marker='s')
plt.scatter(class_1[:,0], class_1[:,1], facecolors='None', edgecolors='black', marker='s')
plt.title('Input data')
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3 f( @5 k) A6 h###############################################
# Train test split and SVM training
from sklearn import cross_validation
2 y! A2 ^9 k/ W  efrom sklearn.svm import SVC
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9 ~% B" i0 W5 l7 h, L( ]' @X_train, X_test, y_train, y_test = cross_validation.train_test_split(X, y, test_size=0.25, random_state=5)
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& \0 R1 I% O- G0 f#params = {'kernel': 'linear'}
; F+ U7 a: X2 U0 w- @#params = {'kernel': 'poly', 'degree': 3}
params = {'kernel': 'rbf'}
classifier = SVC(**params)
classifier.fit(X_train, y_train)
utilities.plot_classifier(classifier, X_train, y_train, 'Training dataset')
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( C! R' K! @. S6 O. c0 x+ Vy_test_pred = classifier.predict(X_test)
: t; w. y& ~9 i3 ]1 ]9 D/ X/ ^8 Qutilities.plot_classifier(classifier, X_test, y_test, 'Test dataset')
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0 }7 I3 B: L8 V* a0 T###############################################
# Evaluate classifier performance

2 {# Y5 G$ K3 Tfrom sklearn.metrics import classification_report
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& f; B% _2 J0 F7 D2 V3 Atarget_names = ['Class-' + str(int(i)) for i in set(y)]
6 a. N- k! _. d5 f- a7 ~4 v1 Yprint "\n" + "#"*30
, w+ w0 ?) C' K; Oprint "\nClassifier performance on training dataset\n"
7 W3 T; g9 V; W0 {, D/ ?print classification_report(y_train, classifier.predict(X_train), target_names=target_names)
1 F/ r; H& O. m- b- _print "#"*30 + "\n"

* g) ^3 q7 w! [* L& Uprint "#"*30
% g. T) g1 V0 v2 f; |$ s, W! Bprint "\nClassification report on test dataset\n"
print classification_report(y_test, y_test_pred, target_names=target_names)
( \( ?& @0 c  L& n  d: S6 jprint "#"*30 + "\n"

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jteo21

好片强烈支持

wxw0214

你就我们摸我

正大符

精华帖，力鼎，巨乳

hzfdy

很具有野性

阑珊灯焱

看上去还不错

wongyuro

感觉还是不错

violetrain2

看着图片很有感觉的