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Model_​Inspection_​Examples

Model Inspection with Verified Components for Responsible AI
Data access Select Local Instances (if necessary) Train Model and Sample Partitioned Data based on Component Requirements Explain and Measure Model Behaviours Top: train setBottom: test setopen viewTrainNeural Networkon all features besides sensitive attributeopen viewopen viewCredit scoringdataUndersamplingof the frequent"creditworthy" classmanually select :a set of data pointsor automatically filter: just first few rows in table manually select: one data pointor automatically select:first row in tableremove sensitive attributeremove sensitive attributeremove sensitive attributeopen viewFairness Scorer Partitioning Predictor Global FeatureImportance AutoML Local ExplanationView Row Sampling XAI View CSV Reader Equal Size Sampling Scatter PlotSelection Scatter PlotSelection Column Filter Column Filter Column Filter Table View Data access Select Local Instances (if necessary) Train Model and Sample Partitioned Data based on Component Requirements Explain and Measure Model Behaviours Top: train setBottom: test setopen viewTrainNeural Networkon all features besides sensitive attributeopen viewopen viewCredit scoringdataUndersamplingof the frequent"creditworthy" classmanually select :a set of data pointsor automatically filter: just first few rows in table manually select: one data pointor automatically select:first row in tableremove sensitive attributeremove sensitive attributeremove sensitive attributeopen viewFairness Scorer Partitioning Predictor Global FeatureImportance AutoML Local ExplanationView Row Sampling XAI View CSV Reader Equal Size Sampling Scatter PlotSelection Scatter PlotSelection Column Filter Column Filter Column Filter Table View

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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: paolotamag
Created at: 2020-06-24
On NodePit since: 2022-02-03
Last update: 2024-04-27
Created with KNIME version: v4.5.1
Tags: autoMLintegrated deploymentXAIMLImachine learning interpretabilityexplainable AIcredit scoringfairnessequalized oddsdemographic parityequality of opportunityResponsible AI

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