import array
import numpy as np
from sklearn import datasets
from sklearn import svm
import pickle
from sklearn.externals import joblib
iris = datasets.load_iris()
digits = datasets.load_digits()
print(digits.data)
print(digits.target)
print(digits.data.shape)
print(digits.target.shape)
digits.images[1796]
clf = svm.SVC(gamma = 0.01, C = 100.)
clf.fit(digits.data[:-1], digits.target[:-1])
SVC(C=100.0, cache_size=200, class_weight=None, coef0=0.0,
decision_function_shape=None, degree=3, gamma=0.01, kernel='rbf',
max_iter=-1, probability=False, random_state=None, shrinking=True,
tol=0.001, verbose=False)
clf.predict(digits.data[-1:])
#存储模型,以备下次使用
joblib.dump(clf, 'iris-clf.pkl')
在ipython运行上述代码
array([8])
载入上次训练的成果
from sklearn.externals import joblib
clf3 = joblib.load('iris-clf.pkl')
clf3.predict(digits.data[-1:])
运行,输出
array([8])
与target呼应
[0 1 2 ... 8 9 8]
最后一个数确实是8