我尝试计算我的标注器的准确率。但是，尽管我使用相同的训练和开发数据，每次运行程序时总是得到不同的准确率。这背后的原因是什么？提前谢谢。

with open('train.txt') as f:training_sentences = list(splitter(f))with open('develop.txt') as f:test_sentences = list(splitter(f))...SOME FEATURES AS A LIST OF DICTS...def transform_to_dataset(training_sentences):    X, y = [], []    for tagged in training_sentences:        for index in range(len(tagged)):            X.append(features(untag(tagged), index))            y.append(tagged[index][1])    return X, yX, y = transform_to_dataset(training_sentences)clf = Pipeline([    ('vectorizer', DictVectorizer(sparse=False)),    ('classifier', DecisionTreeClassifier(criterion='entropy'))])clf.fit(X, y)  X_test, y_test = transform_to_dataset(test_sentences)print "Accuracy:", clf.score(X_test, y_test)

回答：

sklearn 的 DecisionTreeClassifier 使用随机数生成器来决定其分裂。如果你想保证每次运行的结果相同，可以设置分类器的random_state参数。