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

gu80542

偶尔换个口味

功夫茶

import numpy as np
( V2 M- f3 U+ o2 Eimport matplotlib.pyplot as plt
' ~! }  w+ e! ?5 `: s& p% R9 \
import utilities

# b! P. _" c, u; B* u# Load input data
4 ~: f* |  M$ [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)
0 ]+ o4 [+ |6 p" ?* I3 B
9 Y3 K! Q; A! H5 k/ y4 N###############################################
# Separate the data into classes based on 'y'
( E8 B4 W& K- u( Y, P+ z- x: X6 u1 xclass_0 = np.array([X[i] for i in range(len(X)) if y[i]==0])
  W$ p+ @) U0 j1 B/ P; fclass_1 = np.array([X[i] for i in range(len(X)) if y[i]==1])

2 h2 t( U3 j6 H/ J, @5 S: M# Plot the input data
# ~( M) h9 g" b' 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')
7 S8 v. Y& p# O" R, x, }  s5 mplt.title('Input data')
8 X1 f7 O9 D. O+ W: V
  J8 r% ?: Y" @' n/ }+ J. S###############################################
" u6 @# j: R3 s# x$ B# a# Train test split and SVM training
) _& i( h, L6 w5 x/ |# O4 n+ Ffrom sklearn import cross_validation
9 }, }9 R) z5 Ufrom sklearn.svm import SVC
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0 g4 A) w+ I% g% n' tX_train, X_test, y_train, y_test = cross_validation.train_test_split(X, y, test_size=0.25, random_state=5)

8 N! F6 R& ]4 }7 O#params = {'kernel': 'linear'}
#params = {'kernel': 'poly', 'degree': 3}
( f3 U1 A" p; z# U) d8 j/ lparams = {'kernel': 'rbf'}
classifier = SVC(**params)
/ c$ Y8 q' z" J2 G+ _/ Oclassifier.fit(X_train, y_train)
utilities.plot_classifier(classifier, X_train, y_train, 'Training dataset')

7 s0 n& P0 q' w7 U. u/ h' cy_test_pred = classifier.predict(X_test)
utilities.plot_classifier(classifier, X_test, y_test, 'Test dataset')
, M, j! _; i0 c
4 W  Y# @" c* r6 l' H/ K( r###############################################
9 K3 }$ L6 P# k  n: L# Evaluate classifier performance
6 r. i4 @2 U2 A3 k: L! W6 t
from sklearn.metrics import classification_report
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$ w& W7 c" X( c! T/ j0 Y6 b# l0 _target_names = ['Class-' + str(int(i)) for i in set(y)]
8 a9 f! K/ O* ]$ Qprint "\n" + "#"*30
; ]: T/ [+ e% _% Y4 [' ~7 a: Q' sprint "\nClassifier performance on training dataset\n"
print classification_report(y_train, classifier.predict(X_train), target_names=target_names)
+ `3 G1 R' u, S1 C$ \. eprint "#"*30 + "\n"
  l" n/ y# _* Y7 v3 ~+ c1 R1 a
print "#"*30
; O  z" F3 \4 x) F, E# }print "\nClassification report on test dataset\n"
3 V) e  `( I+ s! bprint classification_report(y_test, y_test_pred, target_names=target_names)
print "#"*30 + "\n"

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

K小小

牛逼的电视。。。