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www.markhw.com | ||
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algobeans.com
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| | | | | Outliers can be detected by algorithms used for predictions. To illustrate, we use the k-nearest neighbor (kNN) clustering algorithm. | |
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al3xandr3.github.io
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| | | | | Statistical Significance test using Permutation | |
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ssc.io
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| | | | | When a machine learning (ML) model exhibits poor quality (e.g., poor accuracy or fairness), the problem can often be traced back to errors in the training data. Being able to discover the data examples that are the most likely culprits is a fundamental concern that has received a lot of attention recently. One prominent way to measure 'data importance' with respect to model quality is the Shapley value. Unfortunately, existing methods only focus on the ML model in isolation, without considering the broader ML pipeline for data preparation and feature extraction, which appears in the majority of real-world ML code. This presents a major limitation to applying existing methods in practical settings. In this paper, we propose Canonpipe, a method for efficiently... | |
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geekken.blog
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| | | 1 post published by Geek Ken on November 20, 2022 | ||
