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autosklearn/metalearning/files/a_metric_regression_dense/algorithm_runs.arff
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autosklearn/metalearning/files/a_metric_regression_dense/configurations.csv
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autosklearn/metalearning/files/a_metric_regression_dense/description.txt
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,68 +1,68 @@ | ||
| features_cutoff_time: 3600 | ||
| features_cutoff_memory: 3072 | ||
| number_of_feature_steps: 52 | ||
| feature_step NumberOfInstancesWithMissingValues: NumberOfInstancesWithMissingValues, PercentageOfInstancesWithMissingValues | ||
| feature_step LogInverseDatasetRatio: LogInverseDatasetRatio | ||
| feature_step PCASkewnessFirstPC: PCASkewnessFirstPC | ||
| feature_step ClassEntropy: ClassEntropy | ||
| feature_step SymbolsMin: SymbolsMin | ||
| feature_step NumberOfFeaturesWithMissingValues: NumberOfFeaturesWithMissingValues, PercentageOfFeaturesWithMissingValues | ||
| feature_step KurtosisSTD: KurtosisSTD | ||
| feature_step DatasetRatio: DatasetRatio, LogDatasetRatio | ||
| feature_step LandmarkDecisionNodeLearner: LandmarkDecisionNodeLearner | ||
| feature_step NumberOfClasses: NumberOfClasses | ||
| feature_step NumberOfMissingValues: NumberOfMissingValues, PercentageOfMissingValues | ||
| feature_step KurtosisMin: KurtosisMin | ||
| feature_step SkewnessMean: SkewnessMean | ||
| feature_step SymbolsMean: SymbolsMean | ||
| feature_step Skewnesses: SkewnessMin, SkewnessMax, SkewnessMean, SkewnessSTD | ||
| feature_step SkewnessSTD: SkewnessSTD | ||
| feature_step SkewnessMax: SkewnessMax | ||
| feature_step NumberOfFeatures: NumberOfFeatures, LogNumberOfFeatures | ||
| feature_step NumberOfCategoricalFeatures: NumberOfCategoricalFeatures | ||
| feature_step PercentageOfMissingValues: PercentageOfMissingValues | ||
| feature_step ClassEntropy: ClassEntropy | ||
| feature_step PCA: PCAFractionOfComponentsFor95PercentVariance, PCAKurtosisFirstPC, PCASkewnessFirstPC | ||
| feature_step LandmarkLDA: LandmarkLDA | ||
| feature_step ClassProbabilityMax: ClassProbabilityMax | ||
| feature_step KurtosisMax: KurtosisMax | ||
| feature_step Landmark1NN: Landmark1NN | ||
| feature_step LandmarkNaiveBayes: LandmarkNaiveBayes | ||
| feature_step NumberOfMissingValues: NumberOfMissingValues, PercentageOfMissingValues | ||
| feature_step NumSymbols: SymbolsMin, SymbolsMax, SymbolsMean, SymbolsSTD, SymbolsSum | ||
| feature_step PercentageOfFeaturesWithMissingValues: PercentageOfFeaturesWithMissingValues | ||
| feature_step PCAKurtosisFirstPC: PCAKurtosisFirstPC | ||
| feature_step NumberOfNumericFeatures: NumberOfNumericFeatures | ||
| feature_step Kurtosisses: KurtosisMin, KurtosisMax, KurtosisMean, KurtosisSTD | ||
| feature_step RatioNumericalToNominal: RatioNumericalToNominal | ||
| feature_step SkewnessMin: SkewnessMin | ||
| feature_step KurtosisMean: KurtosisMean | ||
| feature_step SkewnessMean: SkewnessMean | ||
| feature_step LogNumberOfFeatures: LogNumberOfFeatures | ||
| feature_step LandmarkDecisionNodeLearner: LandmarkDecisionNodeLearner | ||
| feature_step NumberOfClasses: NumberOfClasses | ||
| feature_step RatioNominalToNumerical: RatioNominalToNumerical | ||
| feature_step LogNumberOfInstances: LogNumberOfInstances | ||
| feature_step SymbolsSTD: SymbolsSTD | ||
| feature_step MissingValues: NumberOfInstancesWithMissingValues, NumberOfFeaturesWithMissingValues, NumberOfMissingValues | ||
| feature_step SymbolsSum: SymbolsSum | ||
| feature_step SymbolsMean: SymbolsMean | ||
| feature_step PCAFractionOfComponentsFor95PercentVariance: PCAFractionOfComponentsFor95PercentVariance | ||
| feature_step NumberOfFeaturesWithMissingValues: NumberOfFeaturesWithMissingValues, PercentageOfFeaturesWithMissingValues | ||
| feature_step ClassProbabilitySTD: ClassProbabilitySTD | ||
| feature_step PCAKurtosisFirstPC: PCAKurtosisFirstPC | ||
| feature_step NumSymbols: SymbolsMin, SymbolsMax, SymbolsMean, SymbolsSTD, SymbolsSum | ||
| feature_step ClassProbabilityMax: ClassProbabilityMax | ||
| feature_step LandmarkRandomNodeLearner: LandmarkRandomNodeLearner | ||
| feature_step LogNumberOfInstances: LogNumberOfInstances | ||
| feature_step Skewnesses: SkewnessMin, SkewnessMax, SkewnessMean, SkewnessSTD | ||
| feature_step RatioNominalToNumerical: RatioNominalToNumerical | ||
| feature_step ClassProbabilityMean: ClassProbabilityMean | ||
| feature_step ClassProbabilitySTD: ClassProbabilitySTD | ||
| feature_step SymbolsMin: SymbolsMin | ||
| feature_step LogInverseDatasetRatio: LogInverseDatasetRatio | ||
| feature_step LandmarkDecisionTree: LandmarkDecisionTree | ||
| feature_step KurtosisMean: KurtosisMean | ||
| feature_step NumberOfInstancesWithMissingValues: NumberOfInstancesWithMissingValues, PercentageOfInstancesWithMissingValues | ||
| feature_step KurtosisMax: KurtosisMax | ||
| feature_step PCASkewnessFirstPC: PCASkewnessFirstPC | ||
| feature_step PCAFractionOfComponentsFor95PercentVariance: PCAFractionOfComponentsFor95PercentVariance | ||
| feature_step LandmarkLDA: LandmarkLDA | ||
| feature_step ClassOccurences: ClassProbabilityMin, ClassProbabilityMax, ClassProbabilityMean, ClassProbabilitySTD | ||
| feature_step KurtosisSTD: KurtosisSTD | ||
| feature_step SkewnessSTD: SkewnessSTD | ||
| feature_step KurtosisMin: KurtosisMin | ||
| feature_step SymbolsSTD: SymbolsSTD | ||
| feature_step NumberOfInstances: NumberOfInstances, LogNumberOfInstances | ||
| feature_step InverseDatasetRatio: InverseDatasetRatio, LogInverseDatasetRatio | ||
| feature_step NumberOfCategoricalFeatures: NumberOfCategoricalFeatures | ||
| feature_step Kurtosisses: KurtosisMin, KurtosisMax, KurtosisMean, KurtosisSTD | ||
| feature_step ClassProbabilityMin: ClassProbabilityMin | ||
| feature_step LogDatasetRatio: LogDatasetRatio | ||
| feature_step LandmarkDecisionTree: LandmarkDecisionTree | ||
| feature_step PercentageOfMissingValues: PercentageOfMissingValues | ||
| feature_step InverseDatasetRatio: InverseDatasetRatio, LogInverseDatasetRatio | ||
| feature_step PercentageOfInstancesWithMissingValues: PercentageOfInstancesWithMissingValues | ||
| feature_step ClassProbabilityMean: ClassProbabilityMean | ||
| feature_step RatioNumericalToNominal: RatioNumericalToNominal | ||
| feature_step PercentageOfFeaturesWithMissingValues: PercentageOfFeaturesWithMissingValues | ||
| feature_step NumberOfInstances: NumberOfInstances, LogNumberOfInstances | ||
| feature_step LogDatasetRatio: LogDatasetRatio | ||
| feature_step SkewnessMin: SkewnessMin | ||
| feature_step NumberOfNumericFeatures: NumberOfNumericFeatures | ||
| feature_step Landmark1NN: Landmark1NN | ||
| feature_step SymbolsMax: SymbolsMax | ||
| feature_step MissingValues: NumberOfInstancesWithMissingValues, NumberOfFeaturesWithMissingValues, NumberOfMissingValues | ||
| feature_step SkewnessMax: SkewnessMax | ||
| feature_step DatasetRatio: DatasetRatio, LogDatasetRatio | ||
| 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: NumberOfInstancesWithMissingValues, LogInverseDatasetRatio, PCASkewnessFirstPC, ClassEntropy, SymbolsMin, NumberOfFeatures, NumberOfCategoricalFeatures, PercentageOfMissingValues, PCA, LandmarkLDA, ClassProbabilityMax, KurtosisMax, Landmark1NN, LandmarkNaiveBayes, NumberOfMissingValues, NumSymbols, PercentageOfFeaturesWithMissingValues, PCAKurtosisFirstPC, NumberOfNumericFeatures, Kurtosisses, RatioNumericalToNominal, SkewnessMin, KurtosisMean, SkewnessMean, LogNumberOfFeatures, LandmarkDecisionNodeLearner, NumberOfClasses, SymbolsSum, SymbolsMean, PCAFractionOfComponentsFor95PercentVariance, NumberOfFeaturesWithMissingValues, ClassProbabilitySTD, LandmarkRandomNodeLearner, LogNumberOfInstances, Skewnesses, RatioNominalToNumerical, ClassProbabilityMean, ClassOccurences, KurtosisSTD, SkewnessSTD, KurtosisMin, SymbolsSTD, NumberOfInstances, InverseDatasetRatio, ClassProbabilityMin, LogDatasetRatio, LandmarkDecisionTree, PercentageOfInstancesWithMissingValues, SymbolsMax, MissingValues, SkewnessMax, DatasetRatio | ||
| default_steps: NumberOfFeaturesWithMissingValues, KurtosisSTD, DatasetRatio, LandmarkDecisionNodeLearner, NumberOfClasses, NumberOfMissingValues, KurtosisMin, SkewnessMean, SymbolsMean, Skewnesses, SkewnessSTD, SkewnessMax, NumberOfFeatures, ClassEntropy, PCA, LandmarkNaiveBayes, LogNumberOfFeatures, RatioNominalToNumerical, LogNumberOfInstances, SymbolsSTD, MissingValues, SymbolsSum, PCAKurtosisFirstPC, NumSymbols, ClassProbabilityMax, LandmarkRandomNodeLearner, ClassProbabilitySTD, SymbolsMin, LogInverseDatasetRatio, LandmarkDecisionTree, KurtosisMean, NumberOfInstancesWithMissingValues, KurtosisMax, PCASkewnessFirstPC, PCAFractionOfComponentsFor95PercentVariance, LandmarkLDA, ClassOccurences, NumberOfCategoricalFeatures, Kurtosisses, ClassProbabilityMin, PercentageOfMissingValues, InverseDatasetRatio, PercentageOfInstancesWithMissingValues, ClassProbabilityMean, RatioNumericalToNominal, PercentageOfFeaturesWithMissingValues, NumberOfInstances, LogDatasetRatio, SkewnessMin, NumberOfNumericFeatures, Landmark1NN, SymbolsMax | ||
|
|
||
| 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 | ||
| performance_type: solution_quality | ||
| performance_measures: a_metric | ||
| algorithms_stochastic: | ||
|
|
||
| scenario_id: openml | ||
| scenario_id: ChaLearn_AutoML_Challenge_2015 | ||
| maximize: false | ||
| algorithm_cutoff_time: 1800 | ||
| algorithm_cutoff_time: 3600 | ||
| algorithm_cutoff_memory: 3072 |
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