r""" For PCA model, apply dimensionality reduction to given data. Parameters ---------- X : array-like, shape (n_samples, p_features) Sample matrix to be transformed.
(self, X)
| 146 | return tags |
| 147 | |
| 148 | def transform(self, X): |
| 149 | r""" |
| 150 | For PCA model, apply dimensionality reduction |
| 151 | to given data. |
| 152 | |
| 153 | Parameters |
| 154 | ---------- |
| 155 | X : array-like, shape (n_samples, p_features) |
| 156 | Sample matrix to be transformed. |
| 157 | |
| 158 | """ |
| 159 | X = new_data_check(self, X) |
| 160 | |
| 161 | return X.dot(self.coef_) |
| 162 | |
| 163 | def ratio(self, X): |
| 164 | r""" |