本文整理汇总了Python中sklearn.preprocessing.LabelEncoder.get_params方法的典型用法代码示例。如果您正苦于以下问题：Python LabelEncoder.get_params方法的具体用法？Python LabelEncoder.get_params怎么用？Python LabelEncoder.get_params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.preprocessing.LabelEncoder的用法示例。
在下文中一共展示了LabelEncoder.get_params方法的2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: one_click_transform
# 需要导入模块: from sklearn.preprocessing import LabelEncoder [as 别名]
# 或者: from sklearn.preprocessing.LabelEncoder import get_params [as 别名]
def one_click_transform(data):
enc = LabelEncoder()
label_encoder = enc.fit(data[0:])
float_class = label_encoder.transform(data[0:]).astype(float)
print "[INFO] Transforming Success, Categories Generated "
print "[INFO] MAPPING: ", enc.get_params(deep = True)
return float_class示例2: read_file_and_get_labels
# 需要导入模块: from sklearn.preprocessing import LabelEncoder [as 别名]
# 或者: from sklearn.preprocessing.LabelEncoder import get_params [as 别名]
fout.close()
print "Phase1:",
labels1, labels2 = read_file_and_get_labels(input_fname, wanted_lines)
# create the label encoders (mapping from big_integer_labels -> consecutive_small_integer_label
L1_encoder = LabelEncoder();L1_encoder.fit(labels1)
L2_encoder = LabelEncoder();L2_encoder.fit(labels2)
print L1_encoder.get_params()
print "DONE \nLabel counts of",wanted_lines,"lines are: \n\t" , len(L1_encoder.classes_), len(L2_encoder.classes_)
print "\tmax class label values: ", max(L1_encoder.classes_), max(L2_encoder.classes_)
# with open("labels_1.csv","w+") as l1f:
# # convert to list of strings
# label_strings = map(str, L1_encoder.classes_.tolist())
# l1f.write(",".join(label_strings))
#
# with open("labels_2.csv","w+") as l1f:
# label_strings = map(str, L2_encoder.classes_.tolist())
# l1f.write(",".join(label_strings))