(1060, 8) (265, 8)

AutoML directory: AutoML_1
The task is regression with evaluation metric rmse
AutoML will use algorithms: ['Baseline', 'Linear', 'Decision Tree', 'Random Forest', 'Xgboost', 'Neural Network']
AutoML will ensemble availabe models
AutoML steps: ['simple_algorithms', 'default_algorithms', 'ensemble']
* Step simple_algorithms will try to check up to 3 models
1_Baseline rmse 0.933119 trained in 0.12 seconds
2_DecisionTree rmse 0.604529 trained in 8.69 seconds
3_Linear rmse 0.640778 trained in 2.3 seconds
* Step default_algorithms will try to check up to 3 models
4_Default_RandomForest rmse 0.584858 trained in 5.53 seconds
5_Default_Xgboost rmse 0.582731 trained in 2.88 seconds
6_Default_NeuralNetwork rmse 0.64666 trained in 5.2 seconds
* Step ensemble will try to check up to 1 model
Ensemble rmse 0.579981 trained in 0.12 seconds
AutoML fit time: 27.45 seconds

AutoML directory: AutoML_2
The task is regression with evaluation metric rmse
AutoML will use algorithms: ['Random Forest', 'Xgboost']
AutoML will stack models
AutoML will ensemble availabe models
AutoML steps: ['simple_algorithms', 'default_algorithms', 'not_so_random', 'golden_features', 'insert_random_feature', 'features_selection', 'hill_climbing_1', 'hill_climbing_2', 'ensemble', 'stack', 'ensemble_stacked']
Skip simple_algorithms because no parameters were generated.
* Step default_algorithms will try to check up to 2 models
1_Default_RandomForest rmse 0.596139 trained in 7.92 seconds
2_Default_Xgboost rmse 0.584039 trained in 1.59 seconds
* Step not_so_random will try to check up to 18 models
3_Xgboost rmse 0.599567 trained in 4.96 seconds
4_Xgboost rmse 0.593866 trained in 2.01 seconds
5_Xgboost rmse 0.593954 trained in 1.53 seconds
6_Xgboost rmse 0.596786 trained in 2.01 seconds
7_Xgboost rmse 0.589096 trained in 1.93 seconds
8_Xgboost rmse 0.603613 trained in 1.65 seconds
9_Xgboost rmse 0.607813 trained in 1.82 seconds
10_Xgboost rmse 0.596479 trained in 2.32 seconds
11_Xgboost rmse 0.598566 trained in 3.15 seconds
12_RandomForest rmse 0.595774 trained in 6.92 seconds
13_RandomForest rmse 0.601367 trained in 8.41 seconds
14_RandomForest rmse 0.593025 trained in 9.41 seconds
15_RandomForest rmse 0.596608 trained in 9.5 seconds
16_RandomForest rmse 0.591571 trained in 7.94 seconds
17_RandomForest rmse 0.594513 trained in 8.38 seconds
18_RandomForest rmse 0.594856 trained in 6.64 seconds
19_RandomForest rmse 0.596395 trained in 7.75 seconds
20_RandomForest rmse 0.5851 trained in 8.1 seconds
* Step golden_features will try to check up to 1 model
Add Golden Feature: %Agg_diff_DAR
Add Golden Feature: %Agg_diff_Avg.Stability
Add Golden Feature: Avg.Stability_ratio_MutationSite
Add Golden Feature: MutationSite_ratio_Avg.Stability
Add Golden Feature: DAR_diff_Avg.Stability
Created 5 Golden Features in 0.16 seconds.
2_Default_Xgboost_GoldenFeatures rmse 0.583598 trained in 2.04 seconds
* Step insert_random_feature will try to check up to 1 model
2_Default_Xgboost_GoldenFeatures_RandomFeature rmse 0.587742 trained in 3.47 seconds
Drop features ['DAR_diff_Avg.Stability', 'MutationSite_ratio_Avg.Stability', 'Avg.Stability_ratio_MutationSite', 'random_feature', 'Residue_T', 'Residue_L', 'Residue_F', 'Residue_N', 'Residue_Y', 'Linker', 'Residue_P', 'Residue_R', 'Reox', 'Residue_K', 'Residue_Q', 'Residue_I', 'Residue_H', 'Residue_C', 'Residue_D', 'Residue_G', 'Residue_W', 'Residue_A', 'Residue_M', 'Residue_S', 'Residue_E']
* Step features_selection will try to check up to 2 models
20_RandomForest_SelectedFeatures rmse 0.584829 trained in 8.33 seconds
2_Default_Xgboost_GoldenFeatures_SelectedFeatures rmse 0.577184 trained in 1.58 seconds
* Step hill_climbing_1 will try to check up to 7 models
21_RandomForest_SelectedFeatures rmse 0.585223 trained in 7.64 seconds
22_RandomForest rmse 0.591711 trained in 7.91 seconds
23_RandomForest rmse 0.593245 trained in 9.45 seconds
24_RandomForest rmse 0.590171 trained in 6.85 seconds
25_Xgboost_GoldenFeatures_SelectedFeatures rmse 0.574951 trained in 1.61 seconds
26_Xgboost_GoldenFeatures rmse 0.584706 trained in 1.81 seconds
27_Xgboost rmse 0.579199 trained in 1.72 seconds
* Step hill_climbing_2 will try to check up to 4 models
28_RandomForest_SelectedFeatures rmse 0.586703 trained in 5.99 seconds
29_Xgboost_GoldenFeatures_SelectedFeatures rmse 0.575996 trained in 1.61 seconds
30_Xgboost_GoldenFeatures_SelectedFeatures rmse 0.579304 trained in 1.57 seconds
31_Xgboost rmse 0.581736 trained in 1.63 seconds
* Step ensemble will try to check up to 1 model
Ensemble rmse 0.569821 trained in 3.57 seconds
* Step stack will try to check up to 10 models
25_Xgboost_GoldenFeatures_SelectedFeatures_Stacked rmse 0.580141 trained in 2.0 seconds
29_Xgboost_GoldenFeatures_SelectedFeatures_Stacked rmse 0.582319 trained in 2.21 seconds
2_Default_Xgboost_GoldenFeatures_SelectedFeatures_Stacked rmse 0.582473 trained in 2.06 seconds
27_Xgboost_Stacked rmse 0.582971 trained in 2.06 seconds
30_Xgboost_GoldenFeatures_SelectedFeatures_Stacked rmse 0.5845 trained in 1.84 seconds
31_Xgboost_Stacked rmse 0.581005 trained in 2.06 seconds
2_Default_Xgboost_GoldenFeatures_Stacked rmse 0.584416 trained in 2.16 seconds
2_Default_Xgboost_Stacked rmse 0.583641 trained in 2.09 seconds
26_Xgboost_GoldenFeatures_Stacked rmse 0.580362 trained in 2.2 seconds
2_Default_Xgboost_GoldenFeatures_RandomFeature_Stacked rmse 0.585285 trained in 4.73 seconds
* Step ensemble_stacked will try to check up to 1 model
Ensemble_Stacked rmse 0.569267 trained in 6.07 seconds
AutoML fit time: 210.63 seconds