Task: evaluate
Training on train, Test on test, feature set ['example_iris_features'] ...
	featurizing and training new LogisticRegression model
	best f1_score_micro grid search score: 0.95
	hyperparameters: C: 100.0, class_weight: None, dual: False, fit_intercept: True, intercept_scaling: 1, max_iter: 100, multi_class: ovr, n_jobs: 1, penalty: l2, random_state: 123456789, solver: liblinear, tol: 0.0001, verbose: 0, warm_start: False
	evaluating predictions
