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March 25, 2020 07:06
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Extend the CCA class of scikit-learn to return reconstructions of the Y as well.
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| from sklearn.cross_decomposition import CCA | |
| from sklearn.utils import check_array | |
| from sklearn.utils.validation import check_is_fitted, FLOAT_DTYPES | |
| class CCA_extended(CCA): | |
| def __init__(self,*args,**kwargs): | |
| super().__init__(*args,**kwargs) | |
| return | |
| def inverse_transform_xy(self,X,Y): | |
| """ | |
| This module calculates the inverse transform for both X and Y | |
| CCA.inverse_transform module only calculates reconstructions for X | |
| """ | |
| check_is_fitted(self) | |
| X = check_array(X, dtype=FLOAT_DTYPES) | |
| Y = check_array(Y, dtype=FLOAT_DTYPES) | |
| x = np.matmul(X, cca.x_loadings_.T) | |
| x *= cca.x_std_ | |
| x += cca.x_mean_ | |
| y = np.matmul(Y, cca.y_loadings_.T) | |
| y *= cca.y_std_ | |
| y += cca.y_mean_ | |
| return x,y |
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