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3 results for “Kernel Choice”
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Research ArticleOpen accessIn the keywordsHYPERPARAMETER SELECTION IN KERNEL PRINCIPAL COMPONENT ANALYSISMd. Ashad Alam, Kenji FukumizuIn kernel methods, choosing a suitable kernel is indispensable for favorable results. No well-founded methods, however, have been established in general for unsupervised learning. We focus on kernel Principal Component Analysis (kernel PCA), which is a nonlinear extension of principal component analysis and has been used electively for extracting nonlinear features and reducing dimensionality. As a kernel method, kernel PCA … …Journal of Computer Science, Vol. 10, Issue 7 · 15 Feb 2014 · 8,721 accessesView PDFCite
Research ArticleOpen accessIn the abstractPM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive EvaluationShrabani Medhi, Minakshi GogoiAir pollution is a global issue. PM2.5 is considered to be the most dangerous pollutant. Prediction of PM2.5 concentration is important so that effective measures can be taken beforehand. A multitude of machine learning methodologies have been employed in forecasting PM2.5 levels, utilizing diverse combinations of ensemble classifiers and regressors. However, there are three important issues that need to be … …Journal of Computer Science, Vol. 20, Issue 9 · 20 Jun 2024 · 5,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved SVM with Hyperparameter Tuning for Fake News DetectionAtcharaporn Nachaithong, Kittipol WisaengIn today’s digital age, accessing information has become effortless. An abundance of resources is available online, from trustworthy news outlets providing factual information to unverified opinions shared by anonymous individuals. With the advent of modern technology, social media platforms have revolutionized interaction and staying informed, providing instant access to news and information related to a wide range of topics. They … …Journal of Computer Science, Vol. 20, Issue 10 · 28 Aug 2024 · 5,636 accessesView PDFCite