scikit-learn

资料：http://scikit-learn.org/dev/documentation.html

因为数学建模的关系，所以才临时了解了Python的一个开源项目 scikit-learn,

有很多东西没有弄懂，以后补充吧

写的第一个测试代码：

import numpy as np
import sys
sys.stdout = open('out.txt', 'w');
from sklearn.ensemble import RandomForestClassifier
f = open('train1.txt', 'r')

data = np.loadtxt(f)
X = data[:, :-1]
y = data[:, -1]

from sklearn import cross_validation
# X = np.array([[1, 2], [3, 4], [1, 2], [3, 4]])
# y = np.array([1, 2, 3, 4])
kf = cross_validation.KFold(99, n_folds=2)
# print len(kf)
# print(kf)

clf = RandomForestClassifier(n_jobs=-1,n_estimators=10)
for train_index, test_index in kf:
    #print("TRAIN:", train_index, "TEST:", test_index)

    X_train, X_test = X[train_index], X[test_index]
    y_train, y_test = y[train_index], y[test_index]

    clf = clf.fit(X_train, y_train)
    ans = clf.predict(X_test)
    print ans
    print y_test