Naeem, MuhammadYu, JianKhan, ZardadAamir, MuhammadZhang, Alan2025-10-272025-10-272025-10-18Applied Soft Computing, ISSN: 1568-4946 (Print), Elsevier BV, 114092-114092. doi: 10.1016/j.asoc.2025.1140921568-4946http://hdl.handle.net/10292/20006With the advancement of the microarray data, reduction in the data dimensions becomes a research hotspot. High-dimensional datasets need to be pre-processed using data reduction techniques. Features selection techniques are used to handle the dimensionality problem. Clustering techniques are also used to reduce the dimensions of data. It selects features highly correlated to the class labels, while less correlated among the features. In this paper, we proposed a new method called the Greedy Heuristic Fuzzy Clustering (GHFClust), which can be used in high dimensional datasets to improve the accuracy and reduce the high dimensionality problems. In this study, the minimum subset of features is selected using the greedy approach, in which interquartile range and relative covering analysis are used. For the remaining data, the fuzzy-c-means clustering technique is used. The results show that the GHFClust has a higher accuracy rate compared to the other methods using benchmark datasets.Copyright © 2025 Elsevier Ltd. All rights reserved. This is the author’s version of a work that was accepted for publication in (see Citation). Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. The definitive version was published in (see Citation). The original publication is available at (see Publisher's Version).4605 Data Management and Data Science46 Information and Computing Sciences4602 Artificial Intelligence4603 Computer Vision and Multimedia Computation0102 Applied Mathematics0801 Artificial Intelligence and Image Processing0806 Information SystemsArtificial Intelligence & Image Processing4602 Artificial intelligence4903 Numerical and computational mathematicsJournal ArticleOpenAccess10.1016/j.asoc.2025.114092