Articles by R on Datentrang

Measuring feature importance in k-means clustering and variants thereof

July 9, 2019 | 0 Comments

We present a novel approach for measuring feature importance in k-means clustering, or variants thereof, to increase the interpretability of clustering results. In supervised machine learning, feature importance is a widely used tool to ensure interpretability of complex models. We adapt this idea to unsupervised learning via partitional clustering. Our ...
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Benchmarking missing data strategies for k-means clustering

June 30, 2019 | 0 Comments

The goal is to compare a few algorithms for missing imputation when used before k-means clustering is performed. For the latter we use the same algorithm as in ClustImpute to ensure that only the computation time of the imputation is compared. In a nutshell, we’ll se that ClustImpute scales ...
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