Method fit_transform

ot/da.py:633–659

r"""Build a coupling matrix from source and target sets of samples :math:`(\mathbf{X_s}, \mathbf{y_s})` and :math:`(\mathbf{X_t}, \mathbf{y_t})` and transports source samples :math:`\mathbf{X_s}` onto target ones :math:`\mathbf{X_t}` Parameters ---------- Xs

(self, Xs=None, ys=None, Xt=None, yt=None)

        return self

    def fit_transform(self, Xs=None, ys=None, Xt=None, yt=None):
        r"""Build a coupling matrix from source and target sets of samples
        :math:`(\mathbf{X_s}, \mathbf{y_s})` and :math:`(\mathbf{X_t}, \mathbf{y_t})`
        and transports source samples :math:`\mathbf{X_s}` onto target ones :math:`\mathbf{X_t}`

        Parameters
        ----------
        Xs : array-like, shape (n_source_samples, n_features)
            The training input samples.
        ys : array-like, shape (n_source_samples,)
            The class labels for training samples
        Xt : array-like, shape (n_target_samples, n_features)
            The training input samples.
        yt : array-like, shape (n_target_samples,)
            The class labels. If some target samples are unlabelled, fill the
            :math:`\mathbf{y_t}`'s elements with -1.

            Warning: Note that, due to this convention -1 cannot be used as a
            class label

        Returns
        -------
        transp_Xs : array-like, shape (n_source_samples, n_features)
            The source samples samples.
        """

        return self.fit(Xs, ys, Xt, yt).transform(Xs, ys, Xt, yt)

    def transform(self, Xs=None, ys=None, Xt=None, yt=None, batch_size=128):
        r"""Transports source samples :math:`\mathbf{X_s}` onto target ones :math:`\mathbf{X_t}`