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Feature Importance

Derive Key QualitiesMethod 5SHAP With RFRAnalysisNode 65Node 66Feature ImportanceBased On???Huge Variance In ScoresSeem IncompehensibleNode 68Feature ImportanceBased On???Huge Variance In ScoresSeem IncompehensibleRun RFR UsingFully Filtered DataRemoving .01 & UnderImproves R2 & MAPEDerive Key QualitiesMethod 1 H2O RFRRequired LocalConvert DataTo H2O FormatConvert BackFrom H2O FormatTESTQUALSold PriceIntegrationPredictionResultsEITLDomain KnowledgeFilterRemove QualitiesBased On UpperCorrelationThresholdTest RemainingQualites ForCorrelationPredictionQualityJoin InitialKey QualitiesTo Sold PrricesBy Liting IDPartition DataTESTFilter ToMAC 2AnalysesOptimizedLVFAfter TestingRemoveAll 0 ColumnsFilter ToTop R2 ScorePartition DataResetRow IDsDerive Key QualitiesMethod 2 RFR Feature Selection Loop Sort ResultsBy Max R2Feature SelectionLoop ToMaximize R2PredictionQualityPrepare ForVisual ComparisonPredictionResultsDerive Key QualitiesMethod 4XGBoost TreeAnalysisChoose R2OR Min ErrorNode 18766Node 18767Node 18769passing RMSE as variableDerive Key QualitiesMethod 3Permutation Importance& Target ShufflingAnalysisexclude targetNode 18773Mean Sale PricePredictionPer Featurelist of headersR2Current RunR2Current Runnumber of permutationsShuffle FeaturesI Must HaveScrewed Up.The Top ResultsAre Pretty MuchThe Opposite Of ExpectationsSort based on importanceChoose R2OR Min ErrorAppendFeature Columnerror differenceNode 18787Node 18788Node 18790ProcessedDataEnd Result Just An Alphabetical List Of Qualities WithoutScoring Or WeightingNode 18793Node 18794Node 18795Feature ImportanceBased on Gain???Node 18797Node 18798Even AfterSeveral IterationsCulling DataMathmaticallyAnd Domain KnowledgeResults Can Seem "Iffy"Just ForKNIME HelpRequestNode 18801RemoveNon FeatureColumnsPartitioning SHAP Loop Start Row Sampling SHAP Loop End Shapley ValuesLoop Start Shapley ValuesLoop End H2O Random ForestLearner (Regression) H2O Local Context Table to H2O H2O to Table Low Variance Filter Excel Reader H2O Predictor(Regression) Column Filter Correlation Filter Linear Correlation Numeric Scorer Joiner H2O Partitioning Low Variance Filter Nominal ValueRow Filter Low Variance Filter Constant ValueColumn Filter Top k Row Filter Partitioning RowID Feature SelectionLoop Start (1:1) Sorter Feature SelectionLoop End Numeric Scorer Cell Splitter Random Forest Predictor(Regression) Partitioning Loop End Numeric Scorer Random Forest Predictor(Regression) Random Forest Predictor(Regression) Partitioning Numeric Scorer Column Filter Table Rowto Variable Column Filter Random Forest Learner(Regression) GroupBy Loop End Table Transposer Row Filter Row Filter Counting Loop Start Target Shuffling Sorter Column NameExtractor Numeric Scorer ConstantValue Column Table Row toVariable Loop Start Math Formula XGBoost Predictor(Regression) XGBoost Tree EnsembleLearner (Regression) Column Filter Excel Reader Table Transposer Random Forest Learner(Regression) Random Forest Predictor(Regression) Random Forest Predictor(Regression) Sorter Column Resorter Column Resorter Sorter Excel Writer Random Forest Learner(Regression) Column Filter Derive Key QualitiesMethod 5SHAP With RFRAnalysisNode 65Node 66Feature ImportanceBased On???Huge Variance In ScoresSeem IncompehensibleNode 68Feature ImportanceBased On???Huge Variance In ScoresSeem IncompehensibleRun RFR UsingFully Filtered DataRemoving .01 & UnderImproves R2 & MAPEDerive Key QualitiesMethod 1 H2O RFRRequired LocalConvert DataTo H2O FormatConvert BackFrom H2O FormatTESTQUALSold PriceIntegrationPredictionResultsEITLDomain KnowledgeFilterRemove QualitiesBased On UpperCorrelationThresholdTest RemainingQualites ForCorrelationPredictionQualityJoin InitialKey QualitiesTo Sold PrricesBy Liting IDPartition DataTESTFilter ToMAC 2AnalysesOptimizedLVFAfter TestingRemoveAll 0 ColumnsFilter ToTop R2 ScorePartition DataResetRow IDsDerive Key QualitiesMethod 2 RFR Feature Selection Loop Sort ResultsBy Max R2Feature SelectionLoop ToMaximize R2PredictionQualityPrepare ForVisual ComparisonPredictionResultsDerive Key QualitiesMethod 4XGBoost TreeAnalysisChoose R2OR Min ErrorNode 18766Node 18767Node 18769passing RMSE as variableDerive Key QualitiesMethod 3Permutation Importance& Target ShufflingAnalysisexclude targetNode 18773Mean Sale PricePredictionPer Featurelist of headersR2Current RunR2Current Runnumber of permutationsShuffle FeaturesI Must HaveScrewed Up.The Top ResultsAre Pretty MuchThe Opposite Of ExpectationsSort based on importanceChoose R2OR Min ErrorAppendFeature Columnerror differenceNode 18787Node 18788Node 18790ProcessedDataEnd Result Just An Alphabetical List Of Qualities WithoutScoring Or WeightingNode 18793Node 18794Node 18795Feature ImportanceBased on Gain???Node 18797Node 18798Even AfterSeveral IterationsCulling DataMathmaticallyAnd Domain KnowledgeResults Can Seem "Iffy"Just ForKNIME HelpRequestNode 18801RemoveNon FeatureColumnsPartitioning SHAP Loop Start Row Sampling SHAP Loop End Shapley ValuesLoop Start Shapley ValuesLoop End H2O Random ForestLearner (Regression) H2O Local Context Table to H2O H2O to Table Low Variance Filter Excel Reader H2O Predictor(Regression) Column Filter Correlation Filter Linear Correlation Numeric Scorer Joiner H2O Partitioning Low Variance Filter Nominal ValueRow Filter Low Variance Filter Constant ValueColumn Filter Top k Row Filter Partitioning RowID Feature SelectionLoop Start (1:1) Sorter Feature SelectionLoop End Numeric Scorer Cell Splitter Random Forest Predictor(Regression) Partitioning Loop End Numeric Scorer Random Forest Predictor(Regression) Random Forest Predictor(Regression) Partitioning Numeric Scorer Column Filter Table Rowto Variable Column Filter Random Forest Learner(Regression) GroupBy Loop End Table Transposer Row Filter Row Filter Counting Loop Start Target Shuffling Sorter Column NameExtractor Numeric Scorer ConstantValue Column Table Row toVariable Loop Start Math Formula XGBoost Predictor(Regression) XGBoost Tree EnsembleLearner (Regression) Column Filter Excel Reader Table Transposer Random Forest Learner(Regression) Random Forest Predictor(Regression) Random Forest Predictor(Regression) Sorter Column Resorter Column Resorter Sorter Excel Writer Random Forest Learner(Regression) Column Filter

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Created by: smart
Created at: 2024-12-17
On NodePit since: 2024-12-18
Last update: 2024-12-18
Created with KNIME version: v5.4.0

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