logistic.py 文件源码

def _intercept_dot(w, X, y):
    """Computes y * np.dot(X, w).
    It takes into consideration if the intercept should be fit or not.
    Parameters
    ----------
    w : ndarray, shape (n_features,) or (n_features + 1,)
        Coefficient vector.
    X : {array-like, sparse matrix}, shape (n_samples, n_features)
        Training data.
    y : ndarray, shape (n_samples,)
        Array of labels.
    """
    c = 0.
    if w.size == X.shape[1] + 1:
        c = w[-1]
        w = w[:-1]

    z = safe_sparse_dot(X, w) + c
    return w, c, y * z