An efficient method to improve the clustering performance using hybrid robust principal component analysis-spectral biclustering in rainfall patterns identification

• 主要な著者: Shaharudin, S. M., Ismail, S., Che Mat Nor, S. M., Ahmad, N.
• フォーマット: 論文
• 言語: English
• 出版事項: Institute of Advanced Engineering and Science 2019
• 主題: QA Mathematics
• オンライン･アクセス: http://eprints.utm.my/id/eprint/90555/1/ShazlynMilleanaShaharudin2019_AnEfficientMethodtoImprovetheClustering.pdf; http://eprints.utm.my/id/eprint/90555/; http://dx.doi.org/10.11591/ijai.v8.i3.pp237-243

In this study, hybrid RPCA-spectral biclustering model is proposed in identifying the Peninsular Malaysia rainfall pattern. This model is a combination between Robust Principal Component Analysis (RPCA) and biclustering in order to overcome the skewness problem that existed in the Peninsular Malaysi...