laplacian_rls.py 文件源码

def fit(self, X, y, L):
        """Fit the model according to the given training data.

        Prameters
        ---------
        X : array-like, shpae = [n_samples, n_features]
            Training data.

        y : array-like, shpae = [n_samples]
            Target values (unlabeled points are marked as 0).

        L : array-like, shpae = [n_samples, n_samples]
            Graph Laplacian.
        """

        labeled               = y != 0
        y_labeled             = y[labeled]
        n_samples, n_features = X.shape
        n_labeled_samples     = y_labeled.size
        I                     = sp.eye(n_samples)
        J                     = sp.diags(labeled.astype(np.float64))
        K                     = rbf_kernel(X, gamma=self.gamma_k)
        M                     = J @ K \
            + self.gamma_a * n_labeled_samples * I \
            + self.gamma_i * n_labeled_samples / n_samples**2 * L**self.p @ K

        # Train a classifer
        self.dual_coef_       = LA.solve(M, y)

        return self