Icon

Example

Choose the variableto optimizeDo the final filtering hereConfigure your setof columns hereCalculateROC & AUCNormalizepredictorsSens, Sp,PPV, NPVVarianceoptimizationOptimalvariance10-fold CVpartition10-fold CVaggregatorDropcorr>=0.80PearsonCCSens, Sp,PPV, NPVLRlearnerLRpredictor10-fold CVaggregatorSens, Sp,PPV, NPVCalculateROC & AUCOptimal Costand Sigma10-fold CVaggregator10-fold CVpartitionSVMpredictorOptimize Costand SigmaSVMlearnerConvertto varCalculateROC & AUCUnivariatedescriptiveFilter outvar <= 0.100Join RFand LRJoin previouswith SVMNamecolumnsCombinationof ROC & AUCExporrting CvsM2 corr in excelRFlearnerRFpredictorCM210-fold CVpartitionConvertto varSort predictorsby coeff Dropcorr>= 0.4PearsonCC for SVMNode 71Feature SelectionLoop End Feature SelectionFilter Partitioning Scorer Feature SelectionLoop Start (1:1) ROC Curve DecisionTree Learner Decision TreePredictor Normalizer Scorer Parameter OptimizationLoop Start ParameterOptimization Loop End X-Partitioner X-Aggregator Correlation Filter Linear Correlation Scorer LogisticRegression Learner Logistic RegressionPredictor X-Aggregator Scorer ROC Curve ParameterOptimization Loop End X-Aggregator X-Partitioner SVM Predictor Parameter OptimizationLoop Start SVM Learner Table Rowto Variable ROC Curve Data Explorer Low Variance Filter Joiner Joiner Column Rename ROC Curve Excel Writer (XLS) Tree EnsembleLearner Tree EnsemblePredictor Excel Reader (XLS) X-Partitioner Table Rowto Variable Sorter Correlation Filter Linear Correlation Partitioning Choose the variableto optimizeDo the final filtering hereConfigure your setof columns hereCalculateROC & AUCNormalizepredictorsSens, Sp,PPV, NPVVarianceoptimizationOptimalvariance10-fold CVpartition10-fold CVaggregatorDropcorr>=0.80PearsonCCSens, Sp,PPV, NPVLRlearnerLRpredictor10-fold CVaggregatorSens, Sp,PPV, NPVCalculateROC & AUCOptimal Costand Sigma10-fold CVaggregator10-fold CVpartitionSVMpredictorOptimize Costand SigmaSVMlearnerConvertto varCalculateROC & AUCUnivariatedescriptiveFilter outvar <= 0.100Join RFand LRJoin previouswith SVMNamecolumnsCombinationof ROC & AUCExporrting CvsM2 corr in excelRFlearnerRFpredictorCM210-fold CVpartitionConvertto varSort predictorsby coeff Dropcorr>= 0.4PearsonCC for SVMNode 71Feature SelectionLoop End Feature SelectionFilter Partitioning Scorer Feature SelectionLoop Start (1:1) ROC Curve DecisionTree Learner Decision TreePredictor Normalizer Scorer Parameter OptimizationLoop Start ParameterOptimization Loop End X-Partitioner X-Aggregator Correlation Filter Linear Correlation Scorer LogisticRegression Learner Logistic RegressionPredictor X-Aggregator Scorer ROC Curve ParameterOptimization Loop End X-Aggregator X-Partitioner SVM Predictor Parameter OptimizationLoop Start SVM Learner Table Rowto Variable ROC Curve Data Explorer Low Variance Filter Joiner Joiner Column Rename ROC Curve Excel Writer (XLS) Tree EnsembleLearner Tree EnsemblePredictor Excel Reader (XLS) X-Partitioner Table Rowto Variable Sorter Correlation Filter Linear Correlation Partitioning

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Usuario
Created at: 2020-07-22
On NodePit since: 2022-02-06
Last update: 2024-04-27
Created with KNIME version: v4.1.3

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!