b0fbaafddcb5a67eb3e4e093974c546324ccb5d0,pyglmnet/pyglmnet.py,,_mu,#Any#Any#Any#Any#,93

Before Change

def _mu(distr, z, eta, fit_intercept):
    The non-linearity (inverse link).
    if distr in ["softplus", "gamma", "neg-binomial"]:
        mu = log1p(np.exp(z))
    elif distr == "poisson":
        mu = z.copy()
        beta0 = (1 - eta) * np.exp(eta) if fit_intercept else 0.
        mu[z > eta] = z[z > eta] * np.exp(eta) + beta0

After Change

        // prevent zeros.
        // https://cran.r-project.org/web/packages/Rmpfr/vignettes/log1mexp-note.pdf
        mu = z.copy()
        mu[z <= 1] = log1p(np.exp(z[z <= 1]))
        mu[z > 1] = (z[z > 1] + log1p(np.exp(-z[z > 1]))) + 1 * 10e-10
    elif distr == "poisson":
        mu = z.copy()
        beta0 = (1 - eta) * np.exp(eta) if fit_intercept else 0.

Instances