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Applying_​Optimized_​Threshold_​from_​Binary_​Calssification_​Inspector

Applying Optimized Threshold from Binary Calssification Inspector
Almost ready for deployment workflow Data Scientist workflow no interactionswhere appliedto this viewselect gradient boosted treesselect the threshold columnnew data where Target column is unkowntrained modelscore new datatake out string prediction from PMML (50% default threshold)apply optimized thresholdtrain data where Target column is knownand Predictions are already applied Binary ClassificationInspector Row Filter Table Columnto Variable Table Reader PMML Reader PMML Predictor Column Filter Rule Engine Table Reader Almost ready for deployment workflow Data Scientist workflow no interactionswhere appliedto this viewselect gradient boosted treesselect the threshold columnnew data where Target column is unkowntrained modelscore new datatake out string prediction from PMML (50% default threshold)apply optimized thresholdtrain data where Target column is knownand Predictions are already applied Binary ClassificationInspector Row Filter Table Columnto Variable Table Reader PMML Reader PMML Predictor Column Filter Rule Engine Table Reader

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Created by: lars.schweikardt
Created at: 2019-11-21
On NodePit since: 2022-01-11
Last update: 2024-04-28
Created with KNIME version: v4.1.0
Tags: Machine LearningClassificationData MiningDecision TreeBinary Classification InspectorThresholdScoringLogistic RegressionGradient Boosted TreesRandom Forest

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