features_cutoff_time: 3600
features_cutoff_memory: 3072
number_of_feature_steps: 52
feature_step NumberOfInstances: NumberOfInstances, LogNumberOfInstances
feature_step LogNumberOfInstances: LogNumberOfInstances
feature_step NumberOfClasses: NumberOfClasses
feature_step NumberOfFeatures: NumberOfFeatures, LogNumberOfFeatures
feature_step LogNumberOfFeatures: LogNumberOfFeatures
feature_step MissingValues: NumberOfInstancesWithMissingValues, NumberOfFeaturesWithMissingValues, NumberOfMissingValues
feature_step NumberOfInstancesWithMissingValues: NumberOfInstancesWithMissingValues, PercentageOfInstancesWithMissingValues
feature_step PercentageOfInstancesWithMissingValues: PercentageOfInstancesWithMissingValues
feature_step NumberOfFeaturesWithMissingValues: NumberOfFeaturesWithMissingValues, PercentageOfFeaturesWithMissingValues
feature_step PercentageOfFeaturesWithMissingValues: PercentageOfFeaturesWithMissingValues
feature_step NumberOfMissingValues: NumberOfMissingValues, PercentageOfMissingValues
feature_step PercentageOfMissingValues: PercentageOfMissingValues
feature_step NumberOfNumericFeatures: NumberOfNumericFeatures
feature_step NumberOfCategoricalFeatures: NumberOfCategoricalFeatures
feature_step RatioNumericalToNominal: RatioNumericalToNominal
feature_step RatioNominalToNumerical: RatioNominalToNumerical
feature_step DatasetRatio: DatasetRatio, LogDatasetRatio
feature_step LogDatasetRatio: LogDatasetRatio
feature_step InverseDatasetRatio: InverseDatasetRatio, LogInverseDatasetRatio
feature_step LogInverseDatasetRatio: LogInverseDatasetRatio
feature_step ClassOccurences: ClassProbabilityMin, ClassProbabilityMax, ClassProbabilityMean, ClassProbabilitySTD
feature_step ClassProbabilityMin: ClassProbabilityMin
feature_step ClassProbabilityMax: ClassProbabilityMax
feature_step ClassProbabilityMean: ClassProbabilityMean
feature_step ClassProbabilitySTD: ClassProbabilitySTD
feature_step NumSymbols: SymbolsMin, SymbolsMax, SymbolsMean, SymbolsSTD, SymbolsSum
feature_step SymbolsMin: SymbolsMin
feature_step SymbolsMax: SymbolsMax
feature_step SymbolsMean: SymbolsMean
feature_step SymbolsSTD: SymbolsSTD
feature_step SymbolsSum: SymbolsSum
feature_step Kurtosisses: KurtosisMin, KurtosisMax, KurtosisMean, KurtosisSTD
feature_step KurtosisMin: KurtosisMin
feature_step KurtosisMax: KurtosisMax
feature_step KurtosisMean: KurtosisMean
feature_step KurtosisSTD: KurtosisSTD
feature_step Skewnesses: SkewnessMin, SkewnessMax, SkewnessMean, SkewnessSTD
feature_step SkewnessMin: SkewnessMin
feature_step SkewnessMax: SkewnessMax
feature_step SkewnessMean: SkewnessMean
feature_step SkewnessSTD: SkewnessSTD
feature_step ClassEntropy: ClassEntropy
feature_step LandmarkLDA: LandmarkLDA
feature_step LandmarkNaiveBayes: LandmarkNaiveBayes
feature_step LandmarkDecisionTree: LandmarkDecisionTree
feature_step LandmarkDecisionNodeLearner: LandmarkDecisionNodeLearner
feature_step LandmarkRandomNodeLearner: LandmarkRandomNodeLearner
feature_step Landmark1NN: Landmark1NN
feature_step PCA: PCAFractionOfComponentsFor95PercentVariance, PCAKurtosisFirstPC, PCASkewnessFirstPC
feature_step PCAFractionOfComponentsFor95PercentVariance: PCAFractionOfComponentsFor95PercentVariance
feature_step PCAKurtosisFirstPC: PCAKurtosisFirstPC
feature_step PCASkewnessFirstPC: PCASkewnessFirstPC
features_deterministic: NumberOfInstances, LogNumberOfInstances, NumberOfClasses, NumberOfFeatures, LogNumberOfFeatures, NumberOfInstancesWithMissingValues, PercentageOfInstancesWithMissingValues, NumberOfFeaturesWithMissingValues, PercentageOfFeaturesWithMissingValues, NumberOfMissingValues, PercentageOfMissingValues, NumberOfNumericFeatures, NumberOfCategoricalFeatures, RatioNumericalToNominal, RatioNominalToNumerical, DatasetRatio, LogDatasetRatio, InverseDatasetRatio, LogInverseDatasetRatio, ClassProbabilityMin, ClassProbabilityMax, ClassProbabilityMean, ClassProbabilitySTD, SymbolsMin, SymbolsMax, SymbolsMean, SymbolsSTD, SymbolsSum, KurtosisMin, KurtosisMax, KurtosisMean, KurtosisSTD, SkewnessMin, SkewnessMax, SkewnessMean, SkewnessSTD, ClassEntropy, LandmarkLDA, LandmarkNaiveBayes, LandmarkDecisionTree, LandmarkDecisionNodeLearner, LandmarkRandomNodeLearner, Landmark1NN, PCAFractionOfComponentsFor95PercentVariance, PCAKurtosisFirstPC, PCASkewnessFirstPC
features_stochastic: 
default_steps: NumberOfInstances, LogNumberOfInstances, NumberOfClasses, NumberOfFeatures, LogNumberOfFeatures, MissingValues, NumberOfInstancesWithMissingValues, PercentageOfInstancesWithMissingValues, NumberOfFeaturesWithMissingValues, PercentageOfFeaturesWithMissingValues, NumberOfMissingValues, PercentageOfMissingValues, NumberOfNumericFeatures, NumberOfCategoricalFeatures, RatioNumericalToNominal, RatioNominalToNumerical, DatasetRatio, LogDatasetRatio, InverseDatasetRatio, LogInverseDatasetRatio, ClassOccurences, ClassProbabilityMin, ClassProbabilityMax, ClassProbabilityMean, ClassProbabilitySTD, NumSymbols, SymbolsMin, SymbolsMax, SymbolsMean, SymbolsSTD, SymbolsSum, Kurtosisses, KurtosisMin, KurtosisMax, KurtosisMean, KurtosisSTD, Skewnesses, SkewnessMin, SkewnessMax, SkewnessMean, SkewnessSTD, ClassEntropy, LandmarkLDA, LandmarkNaiveBayes, LandmarkDecisionTree, LandmarkDecisionNodeLearner, LandmarkRandomNodeLearner, Landmark1NN, PCA, PCAFractionOfComponentsFor95PercentVariance, PCAKurtosisFirstPC, PCASkewnessFirstPC

algorithms_deterministic: 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129
algorithms_stochastic: 
performance_measures: f1_macro
performance_type: solution_quality

scenario_id: auto-sklearn
maximize: false
algorithm_cutoff_time: 1800
algorithm_cutoff_memory: 3072
