[英]Python fit_transform return only zeros
I'm trying to fit_transform an Numpy array, but when run fit_transfort()
, it will fill only zero values.我正在尝试 fit_transform 一个 Numpy 数组,但是当运行fit_transfort()
时,它只会填充零值。
data = [[3],[9],[3],[12],[3],[8],[8],[13],[12],[2],[0],['42'],['58'],[12],[12],[6],[3],[6],[4],[7],[10]];
data=np.array(data).reshape(1, -1)
scaler = MinMaxScaler()
data_fit = scaler.fit_transform(data)
pred_prova=ll.predict(data_fit)
X_test_std[0] # <---- it is right and return from X_train_std = ss.fit_transform(X_train)
array([-0.23130257, 0.19945477, -0.49045489, -2.40903789, 0.62833204, ........数组([-0.23130257,0.19945477,-0.49045489,-2.40903789,0.62833204,......
data_fit
array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])数组([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0 ., 0., 0., 0., 0., 0.]])
You don't need to reshape
the data before fit_transform
, do it afterwards您不需要在fit_transform
之前reshape
数据,之后再做
data = [[3],[9],[3],[12],[3],[8],[8],[13],[12],[2],[0],['42'],['58'],[12],[12],[6],[3],[6],[4],[7],[10]]
data=np.array(data)
scaler = MinMaxScaler()
data_fit = scaler.fit_transform(data)
pred_prova=ll.predict(data_fit)
X_test_std[0] # <---- it is right and return from X_train_std = ss.fit_transform(X_train)
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