Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation
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Abstract
This article presents individual conditional expectation (ICE) plots, a tool for visualizing the model estimated by any supervised learning algorithm. Classical partial dependence plots (PDPs) help visualize the average partial relationship between the predicted response and one or more features. In the presence of substantial interaction effects, the partial response relationship can be heterogeneous. Thus, an average curve, such as the PDP, can obfuscate the complexity of the modeled relationship. Accordingly, ICE plots refine the PDP by graphing the functional relationship between the predicted response and the feature for individual observations. Specifically, ICE plots highlight the variation in the…
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Keywords
- Suite
- Feature (linguistics)
- Covariate
- Range (aeronautics)
- Computer science
- Artificial intelligence
- R package
- Exploratory data analysis
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