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Decision Tree

Training 70 %Test 30 %StatisticsAccident DataM-2(2010-2020)Convert Variableto Predict to NominalFilter Variablestoo much Correlatedto Variable to PredictNormalizeTraining Data:Z-Score (Gaussian)Apply sameNormalizationto Test DataTrain usinga SVM withPolynomialKernelsPredict Test setand GenerateNormalized Class Distribution===ProbabilitiesPartitioning Scorer ROC Curve (local) CSV Reader String Manipulation Column Filter Normalizer Normalizer (Apply) DecisionTree Learner Decision TreePredictor Training 70 %Test 30 %Statistics Accident DataM-2(2010-2020)Convert Variableto Predict to NominalFilter Variablestoo much Correlatedto Variable to PredictNormalizeTraining Data:Z-Score (Gaussian)Apply sameNormalizationto Test DataTrain usinga SVM withPolynomialKernelsPredict Test setand GenerateNormalized Class Distribution===ProbabilitiesPartitioning Scorer ROC Curve (local) CSV Reader String Manipulation Column Filter Normalizer Normalizer (Apply) DecisionTree Learner Decision TreePredictor

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

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Created by: Muhammad Haroon
Created at: 2021-10-07
On NodePit since: 2022-02-06
Last update: 2024-04-30
Created with KNIME version: v4.4.1

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