Method fit

numpy_ml/trees/dt.py:70–85

Fit a binary decision tree to a dataset. Parameters ---------- X : :py:class:`ndarray ` of shape `(N, M)` The training data of `N` examples, each with `M` features Y : :py:class:`ndarray ` of shape `(N,)`

(self, X, Y)

            raise ValueError("`mse` is a valid criterion only when classifier = False.")

    def fit(self, X, Y):
        """
        Fit a binary decision tree to a dataset.

        Parameters
        ----------
        X : :py:class:`ndarray <numpy.ndarray>` of shape `(N, M)`
            The training data of `N` examples, each with `M` features
        Y : :py:class:`ndarray <numpy.ndarray>` of shape `(N,)`
            An array of integer class labels for each example in `X` if
            self.classifier = True, otherwise the set of target values for
            each example in `X`.
        """
        self.n_classes = max(Y) + 1 if self.classifier else None
        self.n_feats = X.shape[1] if not self.n_feats else min(self.n_feats, X.shape[1])
        self.root = self._grow(X, Y)

    def predict(self, X):
        """