Jambura Journal of Mathematics
Vol 5, No 2: August 2023

Unsupervised Feature Selection Based on Self-configuration Approaches using Multidimensional Scaling

Ridho Ananda (Institut Teknologi Telkom Purwokerto)
Atika Ratna Dewi (Institut Teknologi Telkom Purwokerto)
Maifuza Binti Mohd Amin (Politeknik Port Dickson Negeri Sembilan)
Miftahul Huda (Universitas Bina Bangsa)
Gushelmi Gushelmi (Universitas Putra Indonesia YPTK)

Article Info

Publish Date
01 Aug 2023


Some researchers often collect features so the principal information does not lose. However, many features sometimes cause problems. The truth of analysis results will decrease because of the irrelevant or repetitive features. To overcome it, one of the solutions is feature selection. They are divided into two, namely supervised and unsupervised learning. In supervised, the feature selection can only be carried out on data containing labels. Meanwhile, in unsupervised, there are three approaches correlation, configuration, and variance. This study proposes an unsupervised feature selection by combining correlation and configuration using multidimensional scaling (MDS). The proposed algorithm is MDS-Clustering, which uses hierarchical and non-hierarchical clustering. The result of MDS-clustering is compared with the existing feature selection. There are three schemes in the comparison process, namely, 75\%, 50\%, and 25\% feature selected. The dataset used in this study is the UCI dataset. The validities used are the goodness-of-fit of the proximity matrix (GoFP) and the accuracy of the classification algorithm. The comparison results show that the feature selection proposed is certainly worth recommending as a new approach in the feature selection process. Besides, on certain data, the algorithm can outperform the existing feature selection.

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Journal Info







Jambura Journal of Mathematics (JJoM) is a peer-reviewed journal published by Department of Mathematics, State University of Gorontalo. This journal is available in print and online and highly respects the publication ethic and avoids any type of plagiarism. JJoM is intended as a communication forum ...