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
X_labeled = X[labeled]
y_labeled = y[labeled]
n_samples, n_features = X.shape
n_labeled_samples = y_labeled.size
I = sp.eye(n_features)
M = X_labeled.T @ X_labeled \
+ self.gamma_a * n_labeled_samples * I \
+ self.gamma_i * n_labeled_samples / n_samples**2 * X.T @ L**self.p @ X
# Train a classifer
self.coef_ = LA.solve(M, X_labeled.T @ y_labeled)
return self
linear_laplacian_rls.py 文件源码
python
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