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Attempt1

Optimization has to be integrated by a later point of time First attempt FilterDeviations Parameter optimization with cross validation to find best value for the boosting rounds parameter; Question: can this be integrated into the loops above?? Train and score model with the full training dataset and the optimal value for boosting rounds train / test80 / 20Node 57Node 58Node 60Node 61scorepredictionFind best valuefor Boosting Roundswith Random Searchminimizethe mean MSE10-fold cross validationpredict the leftout foldtrain model on9 foldsvisualize predictionsget best Boosting Roundsconfigurationtrain modelon full training setscore predictionspredict testsetcalculate mean(among other things)remove unusedcolumnsget statisticsas flow variablesNode 289Node 298Node 300train / test80 / 20Node 302Node 303Node 304 Partitioning XGBoost Predictor(Regression) XGBoost Tree EnsembleLearner (Regression) Numeric Scorer Loop End X-Aggregator Parameter OptimizationLoop Start ParameterOptimization Loop End X-Partitioner XGBoost Predictor(Regression) XGBoost Tree EnsembleLearner (Regression) Scatter Plot Table Row to Variable(deprecated) XGBoost Tree EnsembleLearner (Regression) Numeric Scorer(deprecated) XGBoost Predictor(Regression) Statistics Column Filter Table Row to Variable(deprecated) Column ListLoop Start Row Filter Normalizer Partitioning Parameter OptimizationLoop Start ParameterOptimization Loop End CSV Reader Optimization has to be integrated by a later point of time First attempt FilterDeviations Parameter optimization with cross validation to find best value for the boosting rounds parameter; Question: can this be integrated into the loops above?? Train and score model with the full training dataset and the optimal value for boosting rounds train / test80 / 20Node 57Node 58Node 60Node 61scorepredictionFind best valuefor Boosting Roundswith Random Searchminimizethe mean MSE10-fold cross validationpredict the leftout foldtrain model on9 foldsvisualize predictionsget best Boosting Roundsconfigurationtrain modelon full training setscore predictionspredict testsetcalculate mean(among other things)remove unusedcolumnsget statisticsas flow variablesNode 289Node 298Node 300train / test80 / 20Node 302Node 303Node 304 Partitioning XGBoost Predictor(Regression) XGBoost Tree EnsembleLearner (Regression) Numeric Scorer Loop End X-Aggregator Parameter OptimizationLoop Start ParameterOptimization Loop End X-Partitioner XGBoost Predictor(Regression) XGBoost Tree EnsembleLearner (Regression) Scatter Plot Table Row to Variable(deprecated) XGBoost Tree EnsembleLearner (Regression) Numeric Scorer(deprecated) XGBoost Predictor(Regression) Statistics Column Filter Table Row to Variable(deprecated) Column ListLoop Start Row Filter Normalizer Partitioning Parameter OptimizationLoop Start ParameterOptimization Loop End CSV Reader

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Created by: tobia
Created at: 2021-01-02
On NodePit since: 2022-02-06
Last update: 2024-04-23
Created with KNIME version: v4.2.3

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