FTRL Example

This page mirrors examples/ftrl_example.py.

1 Fit An FTRL Classifier

import numpy as np
from pprint import pprint

from crabbymetrics import FTRL

np.set_printoptions(precision=4, suppress=True)

rng = np.random.default_rng(6)
n = 1000
k = 5
beta = np.array([0.8, -1.2, 0.4, 0.0, 0.6])

x = rng.normal(size=(n, k))
logits = x @ beta
probs = 1.0 / (1.0 + np.exp(-logits))
y = rng.binomial(1, probs).astype(np.int32)

model = FTRL(alpha=0.1, beta=1.0, l1_ratio=1.0, l2_ratio=1.0)
model.fit(x, y)

print("true coef:", beta)
pprint(model.summary())

true coef: [ 0.8 -1.2  0.4  0.   0.6]
{'coef': array([ 0.0986, -0.0992,  0.0974,  0.0829,  0.0978]),
 'coef_se': array([0.0633, 0.0638, 0.0633, 0.0645, 0.0639])}