polylearn.kernels.anova_kernel(X, P, degree=2)[source]¶ANOVA kernel between X and P:
K_A(x, p) = sum_i1>i2>...>id x_i1 p_i1 x_i2 p_i2 ... x_id p_id
See John Shawe-Taylor and Nello Cristianini, Kernel Methods for Pattern Analysis section 9.2.
| Parameters: | X : ndarray of shape (n_samples_1, n_features) Y : ndarray of shape (n_samples_2, n_features) degree : int, default 2 |
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| Returns: | Gram matrix : array of shape (n_samples_1, n_samples_2) |