本文整理汇总了Python中sklearn.pipeline.Pipeline.accur方法的典型用法代码示例。如果您正苦于以下问题：Python Pipeline.accur方法的具体用法？Python Pipeline.accur怎么用？Python Pipeline.accur使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sklearn.pipeline.Pipeline的用法示例。
在下文中一共展示了Pipeline.accur方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: train_pair
# 需要导入模块: from sklearn.pipeline import Pipeline [as 别名]
# 或者: from sklearn.pipeline.Pipeline import accur [as 别名]
def train_pair(self, p, q):
if p > q:
p, q = q, p
p_len = len(self.by_domain_data[p])
q_len = len(self.by_domain_data[q])
_logger.info("Training SVM for %s V.S. %s, %d + %d = %d recored" % \
(p, q, p_len, q_len, p_len + q_len))
X = list(self.by_domain_data[p])
X.extend(self.by_domain_data[q])
y = [p] * p_len
y.extend([q] * q_len)
pipeline = Pipeline([
("vert", TfidfVectorizer(min_df = 1, binary = False, ngram_range = (1, 1),
tokenizer = Tokenizer())),
("svm", LinearSVC(loss='l2', penalty="l1",
dual=False, tol=1e-3)),
])
if self.cv > 0:
_logger.info("Doing grid search on %d fold CV" % self.cv)
params = {
"svm__C": [1, 10, 50, 100, 500, 1000],
}
grid = GridSearchCV(pipeline, params, cv=self.cv, verbose=50)
grid.fit(X, y)
pipeline = grid.best_estimator_
_logger.info("Grid search got best score:%f" % grid.best_score_)
pipeline.accur = grid.best_score_
else:
pipeline.fit(X, y)
_logger.debug("Testing on training data")
accur = accuracy_score(y, pipeline.predict(X))
pipeline.accur = accur
_logger.info("Trainig accuracy (%s - %s): %f" % (p, q, accur))
self.svms[p,q] = pipeline
return pipeline