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HP: A light-weight hybrid algorithm for accurate data partitioning

Author: Olukanmi, P ; Nelwamondo, Fulufhelo V ; Marwala, T Date: Aug 2020 This paper introduces a hybridization of the k-means and k-medoids paradigms. The new algorithms is named HP (hybrid partitioning) algorithm. Specifically, we improve on a recently developed scalable version of k-means (k-means-lite), by ... Read more
PAM-lite: Fast and accurate k-medoids clustering for massive datasets

Author: Olukanmi, PO ; Nelwamondo, Fulufhelo V ; Marwala, T Date: Jan 2019 The Partitioning Around Medoids (PAM) clustering algorithm is well-known for its robustness and accuracy, but it is computationally expensive. This paper proposes a fast and accurate version, named PAM-lite. Like CLARA which also addresses ... Read more
Performance evaluation of sampling-based large-scale clustering algorithms

Author: Olukanmi, PO ; Nelwamondo, Fulufhelo V ; Marwala, T Date: Jan 2019 Using benchmark datasets, we study the performances of three efficient clustering algorithms which find cluster centers using a fixed number of random samples. The algorithms are also compared with two other (well-known) algorithms, namely ... Read more

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Browsing by Subject "K-medoids"

Browsing by Subject "K-medoids"

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