Function get_p

Logistic-Regression/citreo.py:66–70

(x, w)

# OUTPUT:
#     probability of p(y = 1 | x; w)
def get_p(x, w):
    wTx = 0.
    for i in x:  # do wTx
        wTx += w[i] * 1.  # w[i] * x[i], but if i in x we got x[i] = 1.
    return 1. / (1. + exp(-max(min(wTx, 20.), -20.)))  # bounded sigmoid


# D. Update given model