## Scenario id : OPENML-WEKA-2017-ALGO ## Performance measures : predictive_accuracy ## Performance types : solution_quality ## Algorithm cutoff time : 0 ## Algorithm cutoff mem : NA ## Instance Feature cutoff time : NA ## Instance Feature cutoff mem : NA ## Algorithm Feature cutoff time : NA ## Algorithm Feature cutoff mem : NA ## Nr. of instances : 105 ## Instance Features (deterministic) (103) : MeanAttributeEntropy, NaiveBayesAdwin.warnings, NoiseToSi... ## Instance Features (stochastic) : - ## Algorithm Features (deterministic) ( 26) : Lines..Average., Lines..Total., Size..Average., Size..Tot... ## Algorithm Features (stochastic) : - ## Feature repetitions : 1 - 1 ## Feature costs : No ## Algo. ( 21) : X2361_weka.OneR, X2362_weka.J48, X2364_weka.IBk, X2367_we... ## Algo. repetitions : 1 - 1 ## Algo. runs (inst x algo x rep) : 3150 ## Feature steps : ALL ## CV repetitions : 1 ## CV folds : 10