MCMSTClustering: defining non-spherical clusters by using minimum spanning tree over KD-tree-based micro-clusters

Article Computer Science, Software Engineering

Minimum spanning tree-based cluster analysis: A new algorithm for determining inconsistent edges

Fadi Saar et al.

Summary: This study proposes a new data clustering algorithm that combines MST and critical distance methodology to address the main issue of identifying and removing inconsistent edges, resulting in optimal clusters. Experimental analysis shows that the proposed algorithm outperforms other common data clustering algorithms in terms of overall performance.

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE (2022)

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Editorial Material Computer Science, Software Engineering

Special issue on High Performance Computing Conference (BASARIM-2020)

Ahmet E. Topcu et al.

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE (2022)

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Article Mathematical & Computational Biology

VIASCKDE Index: A Novel Internal Cluster Validity Index for Arbitrary-Shaped Clusters Based on the Kernel Density Estimation

Ali Senol

Summary: The cluster evaluation process is crucial in machine learning and data mining. This study proposes a novel validity index for arbitrary-shaped clusters, which utilizes kernel density estimation and separation-compacntess concepts to accurately measure the quality of clusters.

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2022)

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Article Mathematics, Applied

Analysis and Prediction of College Students' Mental Health Based on K-means Clustering Algorithm

Yanwu Liu

Summary: This paper proposes a psychological management system based on the K-means clustering analysis method, which reuses students' psychological data through data mining, optimizes the iterative process of the K-means algorithm to extract valuable parts, and provides decision guidance for managers to scientifically manage students' mental health process.

APPLIED MATHEMATICS AND NONLINEAR SCIENCES (2022)

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Article Computer Science, Software Engineering

genieclust: Fast and robust hierarchical clustering

Marek Gagolewski

Summary: genieclust is an open source package that implements the Genie hierarchical clustering algorithm in Python and R, which outperforms other approaches in terms of quality and speed. It supports various distances and domains, can be robustified with a noise point detector, and is applicable in diverse research and development activities.

SOFTWAREX (2021)

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Article Geochemistry & Geophysics

A data mining approach for improved interpretation of ERT inverted sections using the DBSCAN clustering algorithm

Kawtar Sabor et al.

Summary: Geophysical imaging using inversion procedures can be challenging due to smoothed sections, but a new approach inspired by data mining, utilizing the DBSCAN algorithm, shows promise in automatically sorting and clustering inverted geophysical models. Through simulation and real field data tests, the effectiveness and potential of this method have been demonstrated.

GEOPHYSICAL JOURNAL INTERNATIONAL (2021)

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Article Mathematics, Applied