学习笔记：支持向量机预测数字

# -*- coding: utf-8 -*-
"""
Created on Tue May  8 16:19:00 2018

@author: eagle
"""

from sklearn.datasets import load_digits
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.svm import LinearSVC 
from sklearn.metrics import classification_report


#加载数据（1797条，8*8像素的图片）
digits = load_digits()
print(digits.data.shape)    

#测试集和训练集分割
X_train,X_test,y_train,y_test = train_test_split(digits.data,digits.target,test_size=0.25,random_state=33)
#y_train.shape 1347
#y_test.shape 450

#对数据进行标准化处理
ss = StandardScaler()
X_train = ss.fit_transform(X_train)
X_test = ss.transform(X_test)

#基于线性假设的支持向量机:初始化、训练、预测
lsvc = LinearSVC()
lsvc.fit(X_train,y_train)
y_predict = lsvc.predict(X_test)

#评价
print('The Accuracy of Linear SVC is:',lsvc.score(X_test,y_test))
print(classification_report(y_test,y_predict,target_names=digits.target_names.astype(str)))