Fit the regression model to the data and targets in `X` and `y`. Parameters ---------- X : :py:class:`ndarray ` of shape `(N, M)` An array of N examples to generate predictions on y : :py:class:`ndarray ` of shape `(
(self, X, y)
| 38 | self.kernel = KernelInitializer(kernel)() |
| 39 | |
| 40 | def fit(self, X, y): |
| 41 | """ |
| 42 | Fit the regression model to the data and targets in `X` and `y`. |
| 43 | |
| 44 | Parameters |
| 45 | ---------- |
| 46 | X : :py:class:`ndarray <numpy.ndarray>` of shape `(N, M)` |
| 47 | An array of N examples to generate predictions on |
| 48 | y : :py:class:`ndarray <numpy.ndarray>` of shape `(N, ...)` |
| 49 | Predicted targets for the `N` rows in `X` |
| 50 | """ |
| 51 | self.parameters = {"X": X, "y": y} |
| 52 | |
| 53 | def predict(self, X): |
| 54 | """ |