LogisticRegression

LogisticRegression# class sklearn.linear_model.LogisticRegression(penalty='l2', *, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=None, random_state=None, solver='lbfgs', max_iter=100, multi_class='deprecated', verbose=0, warm_start=False, n_jobs=None, l1_ratio=None)[source]# Logistic Regression (aka logit, MaxEnt) classifier. This class implements regularized

[call_me_nots]

ああ、デフォルトで正則化してるから結果が違うのか

[somemo]

“penalty : str, ‘l1’ or ‘l2’, default: ‘l2’, C : float, default: 1.0 Inverse of regularization strength; must be a positive float. Like in support vector machines, smaller values specify stronger regularization.”