$ ../ml/pigaios_ml.py -multi -t
[Thu Dec  6 20:50:08 2018] Using the Pigaios Multi Classifier
[Thu Dec  6 20:50:08 2018] Loading data...
[Thu Dec  6 20:50:16 2018] Fitting data with CPigaiosMultiClassifier(None)...
Fitting DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None,
            max_features=None, max_leaf_nodes=None,
            min_impurity_decrease=0.0, min_impurity_split=None,
            min_samples_leaf=1, min_samples_split=2,
            min_weight_fraction_leaf=0.0, presort=False, random_state=None,
            splitter='best')
Fitting BernoulliNB(alpha=1.0, binarize=0.0, class_prior=None, fit_prior=True)
Fitting GradientBoostingClassifier(criterion='friedman_mse', init=None,
              learning_rate=0.1, loss='deviance', max_depth=3,
              max_features=None, max_leaf_nodes=None,
              min_impurity_decrease=0.0, min_impurity_split=None,
              min_samples_leaf=1, min_samples_split=2,
              min_weight_fraction_leaf=0.0, n_estimators=100,
              presort='auto', random_state=None, subsample=1.0, verbose=0,
              warm_start=False)
Fitting RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',
            max_depth=None, max_features='auto', max_leaf_nodes=None,
            min_impurity_decrease=0.0, min_impurity_split=None,
            min_samples_leaf=1, min_samples_split=2,
            min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=1,
            oob_score=False, random_state=None, verbose=0,
            warm_start=False)
[Thu Dec  6 20:54:26 2018] Predicting...
[Thu Dec  6 21:05:14 2018] Correctly predicted 13813 out of 19075 (false negatives 5262 -> 27.585845%, false positives 832 -> 0.083200%)
[Thu Dec  6 21:05:14 2018] Total right matches 1012981 -> 99.402007%
[Thu Dec  6 21:05:14 2018] Saving model...