Summary of Effector: a Python Package For Regional Explanations, by Vasilis Gkolemis et al.
Effector: A Python package for regional explanations
by Vasilis Gkolemis, Christos Diou, Eirini Ntoutsi, Theodore Dalamagas, Bernd Bischl, Julia Herbinger, Giuseppe Casalicchio
First submitted to arxiv on: 3 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents Effector, a Python library designed to analyze the effects of features on model outputs. The library implements global feature effect methods that provide average effects for each feature, which can be misleading when local effects are heterogeneous. To address this issue, regional feature effects offer multiple plots per feature, representing average effects within specific subspaces. These subspaces are defined as hyperrectangles based on logical rules. Effector assesses the heterogeneity of global and regional effect methods, providing reduced heterogeneity in certain subspace regions. The library features a common API for all methods, facilitating comparisons, and its interface is extensible to accommodate new methods. Effector has been thoroughly tested, comes with tutorials, and is available under an open-source license. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Effector is a new tool that helps us understand how different features affect a model’s output. Imagine trying to figure out why someone’s annual income changes as they get older or gain more experience. The problem is that this effect can be different for men and women, or for people with different levels of experience. Effector helps by breaking down these effects into smaller groups, so we can see how each group affects the output in a unique way. It also compares different methods for understanding these effects, making it easier to choose the best one. The tool is easy to use, comes with tutorials, and is free for anyone to use. |
