Sklearn中LabelEncoder与OneHotEncoder

1. LabelEncoder()

# 简单来说 LabelEncoder 是对不连续的数字或者文本进行编号
from sklearn.preprocessing import LabelEncoder
le = LabelEncoder()
le.fit([1,5,67,100])
le.transform([1,1,100,67,5])

array([0,0,3,2,1])

2. OneHotEncoder()

# OneHotEncoder 用于将表示分类的数据扩维:
from sklearn.preprocessing import OneHotEncoder
ohe = OneHotEncoder()
ohe.fit([[1],[2],[3],[4]])
ohe.transform([2],[3],[1],[4]).toarray()

[[0,1,0,0], [0,0,1,0], [1,0,0,0], [0,0,0,1]] 

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转载自blog.csdn.net/zk_j1994/article/details/78496565