本文整理汇总了Python中sklearn.decomposition.TruncatedSVD.clf方法的典型用法代码示例。如果您正苦于以下问题：Python TruncatedSVD.clf方法的具体用法？Python TruncatedSVD.clf怎么用？Python TruncatedSVD.clf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.decomposition.TruncatedSVD的用法示例。
在下文中一共展示了TruncatedSVD.clf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: cluster_testing
# 需要导入模块: from sklearn.decomposition import TruncatedSVD [as 别名]
# 或者: from sklearn.decomposition.TruncatedSVD import clf [as 别名]
def cluster_testing(self, testing):
'''Create RandomTreesEmbedding of data'''
clf = RandomTreesEmbedding(n_estimators=512, random_state=self.seed, max_depth=5)
'''Fit testing data to training model'''
clf.fit = self.clf.fit(testing)
X_transformed = self.clf.fit_transform(testing)
n_components = 2
'''SVD transform data'''
svd = TruncatedSVD(n_components=n_components)
svd.clf = svd.fit(X_transformed)
svd.model = svd.clf.transform(X_transformed)
'''Train transformed data using original model'''
train_transformed = clf.fit.transform(self.train_matrix)
train_model = svd.clf.transform(train_transformed)
'''Generate One Class SVM rejection criteria'''
(clf_OCSVM_t, OCSVMmodel_t) = self.tools.determine_testing_data_similarity(train_model)
predicted = []
'''Remove testing compounds outside rejection margin'''
for i in range(len(svd.model)):
p = OCSVMmodel_t.predict(svd.model[i, :].reshape(1, -1))
pred = OCSVMmodel_t.decision_function(svd.model[i, :].reshape(1, -1)).ravel()
if (p == 1):
predicted.append(i)
return predicted