Randomized Dimensionality Reduction for $k$ -Means Clustering

@article{Boutsidis2015RandomizedDR,
  title={Randomized Dimensionality Reduction for  \$k\$ -Means Clustering},
  author={Christos Boutsidis and Anastasios Zouzias and Michael W. Mahoney and Petros Drineas},
  journal={IEEE Transactions on Information Theory},
  year={2015},
  volume={61},
  pages={1045-1062}
}
  • Christos Boutsidis, Anastasios Zouzias, +1 author Petros Drineas
  • Published 2015
  • Computer Science, Mathematics
  • IEEE Transactions on Information Theory
  • We study the topic of dimensionality reduction for k-means clustering. Dimensionality reduction encompasses the union of two approaches: 1) feature selection and 2) feature extraction. A feature selection-based algorithm for k-means clustering selects a small subset of the input features and then applies k-means clustering on the selected features. A feature extraction-based algorithm for k-means clustering constructs a small set of new artificial features and then applies k-means clustering on… CONTINUE READING

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