JKISeason2-9
Description: In this challenge, your goal is to see which features are the most important in predicting the quality of wine. After doing this analysis, you should create a visualization that shows the features' importances in order.
Solution Summary: I solve this challenge by comparing the root mean squared error obtained with an AutoML regression model over a subset of the data, and over the whole data with feature value permutations -- one feature at a time. In the end, our conclusion is that alcohol content is likely the most important feature that determines wine quality.
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- FeatureKNIME Base nodes
- FeatureKNIME Column Expressions (Labs)
- FeatureKNIME Deep Learning - Keras Integration
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