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2026_Article_RESILINK_ML
Commit fa5b6d99 by Joaquín Irazábal González
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Update model outputs and results for width optimization iterations B29 and B34

- Updated cross-validation results for models in B29 and B34, including new performance metrics and model parameters. - Added new model outputs for Gradient Boosting and SVR in the cv_summary_per_output_B29_H45.csv file. - Introduced new figures and updated manuscript sections to reflect changes in model selection and optimization strategies. - Included new binary files for model outputs and results in both B29 and B34 directories. - Enhanced the Bayesian optimization process description in the manuscript to clarify the methodology and results.
parent da4354ba
Showing with 18 additions and 18 deletions
Code/models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/cv_summary_per_output_B29_H45.csv
output,best_model,cv_rmse,std_rmse,cv_rmse_dispersion,cv_mae,cv_r2,BEST_PARAMS,model_path,train_time_sec,gpr_kernel,selected_by
exymax_tw1,SVR,0.006585985009931142,0.0064982791163432545,0.9866829497097801,0.006585985009931142,,"{""svr__C"": 1245.9545122809943, ""svr__epsilon"": 0.0012027645559314329, ""svr__gamma"": 0.005025785483194675}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_exymax_tw1.joblib,395.13,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
exymax_tw3,SVR,0.006837992343800181,0.004553580884860971,0.6659236594480216,0.006837992343800181,,"{""svr__C"": 448.7880306471758, ""svr__epsilon"": 0.00013403355081127117, ""svr__gamma"": 0.005847007418075073}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_exymax_tw3.joblib,271.87,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
exymax_tw2,SVR,0.0074343683500841745,0.004806222418653051,0.6464869901958292,0.0074343683500841745,,"{""svr__C"": 1578.3879853890564, ""svr__epsilon"": 0.002061045404501547, ""svr__gamma"": 0.003800674800490907}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_exymax_tw2.joblib,357.86,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
tfmmax_frame,SVR,2.619870006205032,2.179555686783801,0.8319327606414179,2.619870006205032,,"{""svr__C"": 5387.889822738673, ""svr__epsilon"": 0.00023269836732785153, ""svr__gamma"": 0.07097468738318204}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_tfmmax_frame.joblib,379.78,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
tfmmax_tw3,SVR,5.238414599827629,6.046768431344908,1.1543126868086917,5.238414599827629,,"{""svr__C"": 5330.328717919815, ""svr__epsilon"": 0.05582902448723831, ""svr__gamma"": 0.04143240634749279}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_tfmmax_tw3.joblib,503.18,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
tfmmax_tw2,GaussianProcess,7.603551373657773,7.080381390450335,0.9311939963975333,7.603551373657773,,"{""gpr__amplitude"": 17.76576664980768, ""gpr__kernel_type"": ""RBF"", ""gpr__length_scale"": 2.467108843522573, ""gpr__n_restarts_optimizer"": 4, ""gpr__noise"": 2.3000512910597964e-12, ""gpr__rq_alpha"": 0.024337729656929853}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_tfmmax_tw2.joblib,593.72,1.91**2 * RBF(length_scale=2.5) + WhiteKernel(noise_level=2.3e-12),lowest_cv_rmse_dispersion_within_5pct_rmse_band
tfmmax_tw1,FlexibleMLP,9.347145297566009,11.923942423962007,1.275677444221071,9.347145297566009,,"{""mlp__activation"": ""relu"", ""mlp__alpha"": 1.9379088771032204e-05, ""mlp__learning_rate_init"": 0.0004224115725246676, ""mlp__n_layers"": 4, ""mlp__n_neurons"": 489}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_tfmmax_tw1.joblib,1210.15,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
exymax_tw1,GradientBoosting,0.00603072181438803,0.0070969169841838655,1.176793956446825,0.00603072181438803,,"{""learning_rate"": 0.04253596650346244, ""max_depth"": 3, ""max_features"": 0.7976937056494365, ""n_estimators"": 415, ""subsample"": 0.7}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_exymax_tw1.joblib,558.4,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
exymax_tw3,GradientBoosting,0.006215295360582448,0.007255618692319494,1.1673811575126103,0.006215295360582448,,"{""learning_rate"": 0.07999999999999999, ""max_depth"": 1, ""max_features"": 1.0, ""n_estimators"": 200, ""subsample"": 0.9}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_exymax_tw3.joblib,508.89,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
exymax_tw2,SVR,0.0074343683500841745,0.004806222418653051,0.6464869901958292,0.0074343683500841745,,"{""svr__C"": 1578.3879853890564, ""svr__epsilon"": 0.002061045404501547, ""svr__gamma"": 0.003800674800490907}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_exymax_tw2.joblib,457.72,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
tfmmax_frame,SVR,2.5401682807293624,1.9339303643963996,0.7613394667856836,2.5401682807293624,,"{""svr__C"": 2392.4696144711884, ""svr__epsilon"": 0.1, ""svr__gamma"": 0.07938429797160905}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_tfmmax_frame.joblib,1041.89,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
tfmmax_tw3,SVR,4.670361578439981,5.422009365315906,1.1609399559866613,4.670361578439981,,"{""svr__C"": 8424.551575529082, ""svr__epsilon"": 0.1, ""svr__gamma"": 0.035969539073433233}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_tfmmax_tw3.joblib,1417.27,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
tfmmax_tw2,SVR,6.756727839118981,6.676538341560321,0.9881319035681159,6.756727839118981,,"{""svr__C"": 10000.0, ""svr__epsilon"": 0.0001, ""svr__gamma"": 0.05217529822341832}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_tfmmax_tw2.joblib,1663.47,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
tfmmax_tw1,FlexibleMLP,10.0635704605035,10.744361421080878,1.067649047944691,10.0635704605035,,"{""mlp__activation"": ""relu"", ""mlp__alpha"": 0.00013301295828297907, ""mlp__learning_rate_init"": 0.00025137486913624557, ""mlp__n_layers"": 5, ""mlp__n_neurons"": 296}",../../models/width_optimization/3W/ml_models/per_output_models_B29_H45/it0/best_model_tfmmax_tw1.joblib,757.86,,lowest_cv_rmse_dispersion_within_5pct_rmse_band
Code/reports/width_optimization/3W/ml_optimization/it0/optimization_results_3W_B29_H45_TFD_W90.csv
......@@ -4,14 +4,14 @@ Configuration_B,29.0
Configuration_H,45.0
Configuration_TFD_W,90.0
Iteration,0.0
tw1_optimal,5.525014015514342
tw2_optimal,8.471896290298302
tw3_optimal,9.333863643334162
Objective_score,-1.1926307429844958e-06
Exy_tw1,0.062156306095972946
Exy_tw2,0.04245576123008932
Exy_tw3,0.04710451673468341
TFM_tw1,90.00000000228151
TFM_tw2,90.00000000327702
TFM_tw3,90.00000000384767
TFM_frame,70.8310257119319
tw1_optimal,5.962169735306373
tw2_optimal,8.231458736581402
tw3_optimal,9.46671346480481
Objective_score,-1.1396992006835905e-06
Exy_tw1,0.051639785547767394
Exy_tw2,0.04546536916285704
Exy_tw3,0.04887117548120472
TFM_tw1,90.00000001877713
TFM_tw2,90.00000003753132
TFM_tw3,90.00000000166554
TFM_frame,70.99551612604436
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