3721aada353b474d5b5ce726fa65de4968fb6b5e,Orange/classification/logistic.py,,,#,79

Before Change

    m = LogisticRegressionSimple(lambda_=2)
    m.fit(iris.X, iris.Y.ravel())
    p_simple = m.predict(iris.X)

    c = LogisticRegressionLearner(lambda_=2)
    l = c(iris)
    p_orange = l(iris)

After Change

    Y[Y == 2.0] = 0.0

    m = LogisticRegressionLearner(lambda_=1.0, normalize=False)
    scores = []
    for tr_ind, te_ind in StratifiedKFold(Y.ravel()):
        s = np.mean(m(data[tr_ind])(data[te_ind]) == data[te_ind].Y.ravel())
        scores.append(s)
    print(np.mean(scores))

Instances