SAGAClassifier vs sklearn liblinear

liblinear_vs_lightning.py

import numpy as np
from lightning.classification import SAGAClassifier
from scipy import sparse

from sklearn.datasets import load_iris, make_classification
from sklearn.linear_model.logistic import (
    LogisticRegression,
)


def test():
    iris = load_iris()
    X, y = iris.data, iris.target
    X = np.concatenate([X] * 10)
    y = np.concatenate([y] * 10)

    X_bin = X[y <= 1]
    y_bin = y[y <= 1] * 2 - 1

    X_sparse, y_sparse = make_classification(n_samples=100, n_features=50,
                                             random_state=0)
    X_sparse = sparse.csr_matrix(X_sparse)

    for penalty in ['l2', 'l1']:
        for (X, y) in ((X_bin, y_bin), (X_sparse, y_sparse)):
            n_samples = X.shape[0]
            for alpha in [1e-4, 0.001, 0.01, 0.1, 1, 10, 100]:
                liblinear = LogisticRegression(
                    C=1. / (n_samples * alpha),
                    solver='liblinear',
                    multi_class='ovr',
                    max_iter=500,
                    fit_intercept=False,
                    penalty=penalty, random_state=0, tol=1e-24)

                if penalty == 'l1':
                    lalpha = 0
                    lbeta = alpha
                    lpenalty = 'l1'
                else:
                    lalpha = alpha
                    lbeta = 0
                    lpenalty = None
                lsaga = SAGAClassifier(loss='log',
                                       beta=lbeta, penalty=lpenalty,
                                       alpha=lalpha,
                                       max_iter=5000,
                                       random_state=0)

                lsaga.fit(X, y)
                liblinear.fit(X, y)
                print('[penalty=%s, alpha=%s, solver=liblinear]' % (penalty, alpha),
                      liblinear.coef_[0, :4])
                print('[penalty=%s, alpha=%s, solver=lightning]' % (penalty, alpha),
                      lsaga.coef_[0, :4])
                print('-------------------------------')

test()