【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
# N; }5 |  k* N4 Timport matplotlib.pyplot as plt
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import utilities
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( ~; {6 P/ u4 b# Load input data
! y9 t4 B- D( c6 H' O6 Uinput_file = 'D:\\1.Modeling material\\Py_Study\\2.code_model\\Python-Machine-Learning-Cookbook\\Python-Machine-Learning-Cookbook-master\\Chapter03\\data_multivar.txt'
' J% o( O1 S2 l% k7 FX, y = utilities.load_data(input_file)
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$ J' Z  M! C8 `) h###############################################
) ]- S. d$ N  D5 q7 a# Separate the data into classes based on 'y'
class_0 = np.array([X[i] for i in range(len(X)) if y[i]==0])
: W2 a4 Q  S$ Q2 y$ Hclass_1 = np.array([X[i] for i in range(len(X)) if y[i]==1])
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# Plot the input data
5 m9 `- I2 C. d/ r0 Nplt.figure()
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')
* a- I5 X; Z- h1 c% l+ x! Q/ Aplt.title('Input data')
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% P* s: j8 T( ^9 z# |###############################################
5 @! _% G0 O! I' q" T' w# Train test split and SVM training
from sklearn import cross_validation
from sklearn.svm import SVC
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) L" k7 Z) |+ G3 gX_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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#params = {'kernel': 'linear'}
#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')

$ W  O5 Y2 W4 e$ M1 dy_test_pred = classifier.predict(X_test)
1 c+ G/ b7 C# V: Z- }+ }  o4 ?utilities.plot_classifier(classifier, X_test, y_test, 'Test dataset')
8 x# e5 p. R2 o$ ^3 f1 r
###############################################
& j2 H4 J7 B& _& h+ _0 w- V# Evaluate classifier performance
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from sklearn.metrics import classification_report
# u3 ^( Z6 C0 ^1 n, v7 @. Z: x2 y" y' a
9 X& }9 L- U. ]& B: X9 p, W% ztarget_names = ['Class-' + str(int(i)) for i in set(y)]
print "\n" + "#"*30
print "\nClassifier performance on training dataset\n"
' i6 ^5 K1 @' _- l0 q8 Uprint classification_report(y_train, classifier.predict(X_train), target_names=target_names)
( |9 K- w2 Y: l8 F, v, f/ {9 Fprint "#"*30 + "\n"
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print "#"*30
7 k/ }" R& T* ]# Wprint "\nClassification report on test dataset\n"
print classification_report(y_test, y_test_pred, target_names=target_names)
4 E8 h9 @' h0 xprint "#"*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