from sklearn.decomposition import DictionaryLearning

#數據預處理字典學習DictionaryLearning模型
def test_DictionaryLearning():
    X=[[1,2,3,4,5],
       [6,7,8,9,10],
       [10,9,8,7,6,],
       [5,4,3,2,1]]
    print("before transform:",X)
    dct=DictionaryLearning(n_components=3)
    dct.fit(X)
    
 
print("components is :",dct.components_)
    print("after transform:",dct.transform(X))
    
# 調用 test_DictionaryLearning
test_DictionaryLearning() 

from sklearn.decomposition import MiniBatchDictionaryLearning

#數據預處理字典學習MiniBatchDictionaryLearning模型
def test_MiniBatchDictionaryLearning():
    X
 
=[[1,2,3,4,5],
       [6,7,8,9,10],
       [10,9,8,7,6,],
       [5,4,3,2,1]]
    print("before transform:",X)
    dct=DictionaryLearning(n_components=3)
    dct.fit(X)
    print("components is :",dct.components_)
    print("after transform:",dct.transform(X))
    
# 調用 test_MiniBatchDictionaryLearning
 

test_MiniBatchDictionaryLearning() 

吳裕雄 python 機器學習——數據預處理字典學習模型