python 中one—hot 三种编码方式

一、什么是One-Hot编码？

     One-Hot编码，又称为一位有效编码，主要是采用N位状态寄存器来对N个状态进行编码，每个状态都由他独立的寄存器位，并且在任意时候只有一位有效。

One-Hot编码是分类变量作为二进制向量的表示。这首先要求将分类值映射到整数值。然后，每个整数值被表示为二进制向量，除了整数的索引之外，它都是零值，它被标记为1。

我们可以使用以下三种方式来实现one-hot

 手动One Hot编码

from numpy import argmax
# define input string
data = 'hello world'
print(data)
# define universe of possible input values
alphabet = 'abcdefghijklmnopqrstuvwxyz '
# define a mapping of chars to integers
char_to_int = dict((c, i) for i, c in enumerate(alphabet))
int_to_char = dict((i, c) for i, c in enumerate(alphabet))
# integer encode input data
integer_encoded = [char_to_int[char] for char in data]
print(integer_encoded)
# one hot encode
onehot_encoded = list()
for value in integer_encoded:
       letter = [0 for _ in range(len(alphabet))]
       letter[value] = 1
       onehot_encoded.append(letter)
print(onehot_encoded)
# invert encoding
inverted = int_to_char[argmax(onehot_encoded[0])]
print(inverted)

基于scikit-learn

from numpy import array
from numpy import argmax
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import OneHotEncoder
# define example
data = ['cold', 'cold', 'warm', 'cold', 'hot', 'hot', 'warm', 'cold', 'warm', 'hot']
values = array(data)
print(values)
# integer encode
label_encoder = LabelEncoder()
integer_encoded = label_encoder.fit_transform(values)
print(integer_encoded)
# binary encode
onehot_encoder = OneHotEncoder(sparse=False)
integer_encoded = integer_encoded.reshape(len(integer_encoded), 1)
onehot_encoded = onehot_encoder.fit_transform(integer_encoded)
print(onehot_encoded)
# invert first example
inverted = label_encoder.inverse_transform([argmax(onehot_encoded[0, :])])
print(inverted)

基于keras

from numpy import array
from numpy import argmax
from keras.utils import to_categorical
# define example
##对字符串
data = ['cold', 'cold', 'warm', 'cold', 'hot', 'hot', 'warm', 'cold', 'warm', 'hot']
values = array(data)
print(values)
# integer encode
label_encoder = LabelEncoder()
integer_encoded = label_encoder.fit_transform(values)
print(integer_encoded)

##对数值
#data=[1, 3, 2, 0, 3, 2, 2, 1, 0, 1]
#data=array(data)
#print(data)

# one hot encode
encoded = to_categorical(integer_encoded)
print(encoded)
# invert encoding
inverted = argmax(encoded[0])
print(inverted)