Icon

JKI_​Challenge-13_​diy

Solution to JKI Challenge 13. This workflow runs an AutoML node and subsequently carries out a Feature Importance to identify the most important components as well as establishes the movement of the target MEDV value in comparison to the Feature attributes utilising the SHAP loop methods.

Feature ImportanceComponent SHAP Loop Application Node 1Node 37Node 38Node 39using k-means to summarize the data to n prototypes rowNode 41Node 42Node 43Node 44Node 45Node 46 CSV Reader FeaImp_Reg SHAP Loop Start Row Sampling Row Sampling SHAP Summarizer Workflow Executor SHAP Loop End Column Rename(Regex) Joiner Column Filter RowID Dependence Plot Dependence_Matlib_Plot Feature ImportanceComponent SHAP Loop Application Node 1Node 37Node 38Node 39using k-means to summarize the data to n prototypes rowNode 41Node 42Node 43Node 44Node 45Node 46 CSV Reader FeaImp_Reg SHAP Loop Start Row Sampling Row Sampling SHAP Summarizer Workflow Executor SHAP Loop End Column Rename(Regex) Joiner Column Filter RowID Dependence Plot Dependence_Matlib_Plot

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: Nilotpal.Choudhury
Created at: 2023-07-02
On NodePit since: 2023-07-02
Last update: 2024-11-23
Created with KNIME version: v4.7.4
Tags: SHAPFeature Importance

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

Try NodePit Runner!