JKISeasor2-19_​tomljh_​ver3

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Challenge 19: Dealing with Diabetes

Level: Easy or Medium

Description: In this challenge you will take the role of a clinician and check if machine learning can help you predict diabetes. You should create a solution that beats a baseline accuracy of 65%, and also works very well for both classes (having diabetes vs not having diabetes). We got an accuracy of 77% with a minimal workflow. If you'd like to take this challenge from easy to medium, try implementing:

* sampling techniques
* feature importance calculation

Nodes

• Partitioning2 ×
• CSV Reader1 ×
• Data Explorer (JavaScript)1 ×
• Feature Selection Filter1 ×
• Feature Selection Loop End1 ×
• Feature Selection Loop Start (1:1)1 ×
• Gradient Boosted Trees Learner1 ×
• Gradient Boosted Trees Predictor1 ×
• Naive Bayes Learner1 ×
• Naive Bayes Predictor1 ×
• Number To String1 ×
• ROC Curve (JavaScript)1 ×
• Reference Column Filter1 ×
• SMOTE1 ×
• Scorer (JavaScript)1 ×
• Scorer1 ×

Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Ensemble Learning Wrappers
• FeatureKNIME JavaScript Views
• FeatureKNIME JavaScript Views (Labs)

Links

• No links available