# viraltab() works Code print(viraltab(x, semilla, target, pliegues, repeticiones, rejilla)) Output wflow_id .config .metric mean std_err n 1 normalized_MARS Preprocessor1_Model1 rmse 191.14 10.86 2 2 normalized_MARS Preprocessor1_Model1 rsq 0.46 0.08 2 3 simple_MARS Preprocessor1_Model1 rmse 191.14 10.86 2 4 simple_MARS Preprocessor1_Model1 rsq 0.46 0.08 2 5 normalized_neural_network Preprocessor1_Model1 rmse 227.01 48.46 2 6 normalized_neural_network Preprocessor1_Model1 rsq 0.26 0.13 2 7 simple_neural_network Preprocessor1_Model1 rmse 241.93 57.78 2 8 simple_neural_network Preprocessor1_Model1 rsq 0.32 0.27 2 9 full_quad_svm_r Preprocessor1_Model1 rmse 243.65 2.32 2 10 full_quad_svm_r Preprocessor1_Model1 rsq 0.27 0.01 2 11 simple_svm_r Preprocessor1_Model1 rmse 243.65 2.32 2 12 simple_svm_r Preprocessor1_Model1 rsq 0.55 0.03 2 13 normalized_svm_r Preprocessor1_Model1 rmse 243.65 2.32 2 14 normalized_svm_r Preprocessor1_Model1 rsq 0.55 0.03 2 15 full_quad_MARS Preprocessor1_Model1 rmse 254.28 78.51 2 16 full_quad_MARS Preprocessor1_Model1 rsq 0.34 0.15 2 17 full_quad_neural_network Preprocessor1_Model1 rmse 503.87 317.21 2 18 full_quad_neural_network Preprocessor1_Model1 rsq 0.17 0.16 2 preprocessor model rank 1 recipe mars 1 2 recipe mars 1 3 workflow_variables mars 2 4 workflow_variables mars 2 5 recipe mlp 3 6 recipe mlp 3 7 workflow_variables mlp 4 8 workflow_variables mlp 4 9 recipe svm_rbf 5 10 recipe svm_rbf 5 11 workflow_variables svm_rbf 6 12 workflow_variables svm_rbf 6 13 recipe svm_rbf 7 14 recipe svm_rbf 7 15 recipe mars 8 16 recipe mars 8 17 recipe mlp 9 18 recipe mlp 9