causally.scm.causal_mechanism.LinearMechanism.predict

LinearMechanism.predict(X: array) → array

Apply a linera transformation on X.

Given a vector x with \(p\) features, the output y is given by:

\[y = \sum_{i=1}^p \alpha_i x_i\]

where \(\alpha_i\) are random coefficients.

Parameters:

X (np.array, shape (num_samples, num_parents)) – Parents’ observtations to be transformed by the causal mechanism.

Returns:

y – The output of the causal mechanism.

Return type:

np.array, shape (num_samples)