one_hot 類別變數中n個不同類別轉換為n個變數
dummy variable 在某一設定的參考準則下，對n個不同的類別，轉換為n-1個變數
pandas 將標籤轉化為獨熱編碼
pd.get_dummies(df_nmf['cluster']).head(20)from keras.utils import to_categorical
encoded=to_categorical(df_nmf['cluster'])
from sklearn.preprocessing import labelencoder
from sklearn.preprocessing import onehotencoder
data = ['cold', 'cold', 'warm', 'cold', 'hot', 'hot', 'warm', 'cold', 'warm', 'hot']
values = np.array(data)
print(values)
# integer encode
label_encoder = labelencoder()
integer_encoded = label_encoder.fit_transform(values)
print(integer_encoded)
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([np.argmax(onehot_encoded[0, :])])
print(inverted)