本文整理汇总了Python中Features.append_features方法的典型用法代码示例。如果您正苦于以下问题：Python Features.append_features方法的具体用法？Python Features.append_features怎么用？Python Features.append_features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Features的用法示例。
在下文中一共展示了Features.append_features方法的8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: feat5
# 需要导入模块: import Features [as 别名]
# 或者: from Features import append_features [as 别名]
def feat5(train, test):
train_valence, test_valence = feat1(train, test)
puncter, train_punct = Features.punctuation(train)
_, test_punct = Features.punctuation(test, vectorizer = puncter)
train_matrix = Features.append_features([train_valence, train_punct])
test_matrix = Features.append_features([test_valence, test_punct])
return train_matrix, test_matrix示例2: feat6_generic
# 需要导入模块: import Features [as 别名]
# 或者: from Features import append_features [as 别名]
def feat6_generic(train, test, train_pos, test_pos):
train_f5, test_f5 = feat5(train, test)
cter, train_cts = Features.keyPOSNGrams(train_pos, ["jj.*", "vb.*"], tf_idf = True)
_, test_cts = Features.keyPOSNGrams(test_pos, ["jj.*", "vb.*"], vectorizer = cter, tf_idf= True)
train_matrix = Features.append_features([train_f5, train_cts])
test_matrix = Features.append_features([test_f5, test_cts])
return train_matrix, test_matrix示例3: feat4
# 需要导入模块: import Features [as 别名]
# 或者: from Features import append_features [as 别名]
def feat4(train, test):
# feature set 3
train_f3, test_f3 = feat3(train, test)
# punctuation
puncter, train_punct = Features.punctuation(train)
_, test_punct = Features.punctuation(test, vectorizer = puncter)
train_matrix = Features.append_features([train_f3, train_punct])
test_matrix = Features.append_features([test_f3, test_punct])
return train_matrix, test_matrix示例4: feat3
# 需要导入模块: import Features [as 别名]
# 或者: from Features import append_features [as 别名]
def feat3(train, test):
# valence info
train_valence, test_valence = feat1(train, test)
# tf idf info
train_cts, test_cts = feat2(train, test)
# combined info
train_matrix = Features.append_features([train_valence, train_cts])
test_matrix = Features.append_features([test_valence, test_cts])
return train_matrix, test_matrix示例5: feat7
# 需要导入模块: import Features [as 别名]
# 或者: from Features import append_features [as 别名]
def feat7(train, test):
normal_train, train_pos = map(list, zip(*train))
normal_test, test_pos = map(list, zip(*test))
train_f5, test_f5 = feat5(normal_train, normal_test)
cter, train_cts = Features.keyPOSNGrams(train_pos, ["jj.*", "vb.*"], tf_idf = True, ngram_range = (1, 2), stop_words = 'english')
_, test_cts = Features.keyPOSNGrams(test_pos, ["jj.*", "vb.*"], vectorizer = cter, tf_idf= True, ngram_range = (1, 2), stop_words = 'english')
train_matrix = Features.append_features([train_f5, train_cts])
test_matrix = Features.append_features([test_f5, test_cts])
return train_matrix, test_matrix示例6: feat7
# 需要导入模块: import Features [as 别名]
# 或者: from Features import append_features [as 别名]
def feat7(train, test):
# feature set 3
train_f5, test_f5 = feat5(train, test)
# punctuation
puncter, train_punct = Features.bagOfWordsSkLearn(train)
_, test_punct = Features.bagOfWordsSkLearn(test, vectorizer = puncter)
train_matrix = Features.append_features([train_f5, train_punct])
test_matrix = Features.append_features([test_f5, test_punct])
return train_matrix, test_matrix示例7: feat6
# 需要导入模块: import Features [as 别名]
# 或者: from Features import append_features [as 别名]
def feat6(train, test):
normal_train, train_pos = map(list, zip(*train))
normal_test, test_pos = map(list, zip(*test))
train_f5, test_f5 = feat5(normal_train, normal_test)
cter, train_cts = Features.keyPOSNGrams(train_pos, ["jj.*", "vb.*"], tf_idf = True)
_, test_cts = Features.keyPOSNGrams(test_pos, ["jj.*", "vb.*"], vectorizer = cter, tf_idf= True)
train_matrix = Features.append_features([train_f5, train_cts])
test_matrix = Features.append_features([test_f5, test_cts])
return train_matrix, test_matrix示例8: extra_features
# 需要导入模块: import Features [as 别名]
# 或者: from Features import append_features [as 别名]
def extra_features(train, test):
# uni and bigrams
state_info, train_ngrams = Features.wordCountsSkLearn(train, ngram_range = (1, 2), stop_words = 'english')
_, test_ngrams = Features.wordCountsSkLearn(test, vectorizer = state_info, ngram_range = (1, 2), stop_words = 'english')
# valence and punctuation
train_valence_punct, test_valence_punct = feat5(train, test)
# train matrix
train_matrix = Features.append_features([train_ngrams, train_valence_punct])
test_matrix = Features.append_features([test_ngrams, test_valence_punct])
return train_matrix, test_matrix