features_cutoff_time: 3600
features_cutoff_memory: 3072
number_of_feature_steps: 42
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
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
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

algorithms_deterministic: 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659,660,661,662,663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699,700,701,702,703,704,705,706,707,708
algorithms_stochastic: 
performance_measures: f1_micro
performance_type: solution_quality

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