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25 articles for “Component Selection”
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Research ArticleOpen accessEvery word in the titleHYPERPARAMETER 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 keywordsSCUTMA: Selecting Components for Unit Testing in Mobile ApplicationsJosias Gomes, Isabel K. Villanes, Silvia M. Ascate et al.Context The source code of a mobile application has several components (i.e., code units) and they have a cost (e.g., test creation and execution) and benefit (e.g., find bug) value for performing unit testing. Problem Choosing in which components unit tests should be done, in order to increase the benefit (effectiveness) and decrease the cost of this activity. Proposal This … …Journal of Computer Science, Vol. 16, Issue 10 · 15 Oct 2020 · 7,015 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnimal Health Prediction Using Hybrid CNN Based BiLSTM Classification Model: A Deep Learning ApproachJ. Rathi, A. SumathiAccurate prediction of animal diseases is vital in veterinary medicine, as it can substantially enhance animal health outcomes and mitigate economic losses, making it a critical task that warrants attention and innovative solutions. This paper proposes a novel approach to animal condition classification, leveraging an Auto-encoder-based feature selection process and an Improved Hybrid Convolutional Neural Networks (CNN) with Bidirectional (Bi-LSTM) … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,481 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer ClassificationSatyabrata Patro, Jyotirmaya Mishra, Bhavani Sankar PandaBreast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classification of breast cancer. Thus, to effectively categorize the breast cancer dataset, machine learning methods are designed and implemented. In previous research, the algorithms have classification accuracy … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,172 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Based Feature Extraction Approaches for Dual Modalities of Autism Spectrum Disorder NeuroimagesMeenakshi Malviya, Chandra J, Nagendra NHigh-dimensional data, lower detection accuracy, susceptibility to manual errors, and the requirement of clinical experts are some drawbacks of conventional classification models available for Autism Spectrum Disorder (ASD) detection. To address these challenges and explore the affiliated information from advanced imaging modalities such as Magnetic Resonance Imaging (MRI) in structural MRI (sMRI) and resting state-functional MRI (rs-fMRI), the study applied … …Journal of Computer Science, Vol. 20, Issue 11 · 28 Sep 2024 · 5,087 accessesView PDFCite
Review ArticleOpen accessIn the abstractHuman Activity Recognition at the Edge: A Systematic Review of Machine Learning Models, Deployment Constraints, and Latency Energy Accuracy Trade offsJose Antonio Rojas Guillén, Wini Ebelin Quispe Bautista, Arturo Gamarra MorenoHuman Activity Recognition (HAR) has become a key component of intelligent healthcare monitoring, assisted living, sports analytics, smart environments, and wearable computing. However, the migration of HAR models from cloud-centered architectures to edge, embedded, mobile, and wearable platforms introduces constraints related to computational capacity, memory footprint, battery consumption, inference time, and real-time responsiveness. This study presents a systematic literature review … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 593 accessesView PDFCite
Research ArticleOpen accessIn the abstractBiomorphological Indicators of Rainbow Trout (Oncorhynchus mykiss) Fry: Comparative Analysis in the Conditions of the Lower Kolsay and Fish FarmsBarakov Rinat Tairovich, Abilov Berdibek Ibragimovich, Assylbekova Saule Zhangirovna et al.Rainbow trout (Oncorhynchus mykiss Walbaum, 1792) is one of the key species in aquaculture of the salmon family due to its high commercial value and the availability of farming technology. This paper presents data on the morphometric characteristics of rainbow trout fry grown in three types of farms in Kazakhstan and wild forms from Lake Lower Kolsay. The comparison was … …OnLine Journal of Biological Sciences, Vol. 26, Issue 1 · 1 Apr 2026 · 1,384 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Feature Reduction Techniques for Enhanced Network Threat Detection in Wireless Sensor NetworksBikash Kalita, Satyajit SarmahThe security of Wireless Sensor Networks (WSNs) is currently seriously threatened by numerous threats. Consequently, a number of applications are offered to regulate data and information sharing along with the related security features that need to be maintained throughout data transfer. This study suggests an intelligent feature reduction methodology based on machine learning that uses Modified Principal Component Analysis (MPCA) … …Journal of Computer Science, Vol. 21, Issue 8 · 10 Oct 2025 · 2,290 accessesView PDFCite
Research ArticleOpen accessIn the abstractComputational Analysis of Genre Effects on Movie Ratings Using MLP AlgorithmsSubir Gupta, Upasana Adhikari, Shefali Varshney, Tanupriya ChoudhuryPredictive analytics are what the entertainment industry depends on so much in prognosticating movie ratings, which is why they inform filmmakers, distributors and stream platforms strategic moves. Traditional prediction models most times only succeed in missing out on the intricate dynamics that are genre-specific to movie ratings thereby leading to inaccuracies and suboptimal decision making. The paper proposes this research … …Journal of Computer Science, Vol. 21, Issue 4 · 19 Mar 2025 · 5,534 accessesView PDFCite
Research ArticleOpen accessIn the abstractEarly Detection and Classification Approach for Plant Diseases based on MultiScale Image DecompositionAssia Ennouni, Noura Ouled Sihamman, My Abdelouahed Sabri, Abdellah AarabThis paper presents a new and powerful approach for detecting and classifying leaf diseases for plant diagnosis with high accuracy. The main contribution of this paper is that a hybrid approach is proposed by using the combination of Partial Differential Equations (PDE) based image decomposition, segmentation, feature extraction, features selection and classification aiming to improve the classification accuracy and provide … …Journal of Computer Science, Vol. 17, Issue 3 · 25 Mar 2021 · 7,205 accessesView PDFCite