Automated Statistical Feature Selection 

This component automatically runs a number of statistical tests in order to calculate a relevance for each of the selected columns. Based on a threshold, […]

IconConsensusXMLIdentificaitonSplitter 

Read or generate FeatureXML-Files with Identification information

IconSmall sample size study -- PCOS 

This workflow attempts to uncover how different biomarkers (e.g., glucose and insulin levels) are associated with PCOS in obese women. In summary, this […]

RF Feature Importance (based on Python Library) 

This Component can be used to visualise the Feature/variable importance in a binary classification sceanrio. It used the Random forest importance calculater […]

IconJKISeason2-13 

There has been no description set for this workflow's metadata.

Icon03_​Titantic_​Prediction_​Explanations 

Model Interpretability, Titanic The workflow demonstrates how to use SHAP, Shapley Values and LIME implemenatations in KNIME 4.0 and generates a basic […]

Icon03_​Titantic_​Prediction_​Explanations 

Model Interpretability, Titanic The workflow demonstrates how to use SHAP, Shapley Values and LIME implemenatations in KNIME 4.0 and generates a basic […]

IconCS-162 Porters Five Forces - Part 02 Threat of Substitutes v05 

CS-162 Porters Five Forces - Part 02 Threat of Substitutes [Case Studies] CS-162 Porters Five Forces - Part 02 Threat of Substitutes Substitute […]

Iconknwf_​breasttumors 

<p><strong>Challenge 18: Explaining Cancer Predictions</strong></p><p><strong>Level: </strong>Hard<br><br><strong>Description: </strong>You work as a […]

IconTitanic_​052_​Phase_​3_​Age 

Titanic: Phase 3 (Data Preparation) Age => Child, KnownAge URL: Data Science Training - Kapitel 5 https://data-science.training/kapitel-5/