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49 results for “Principal Component Analysis (PCA)”
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Research ArticleOpen accessIn the abstractCardiovascular Disease Prediction using Various Machine Learning AlgorithmsDebabrata Swain, Badal Parmar, Hansal Shah et al.Almostone-third of all deaths caused around the world were caused due tocardiovascular diseases. Even if death was not the result, much cost isincurred during the treatment of such diseases. But much of these deaths andtreatments could have been prevented with prior action. Advance knowledge ofthe symptoms and consequently proper care can lead us to avoid such diseases.Thus, current research proposes … …Journal of Computer Science, Vol. 18, Issue 10 · 13 Oct 2022 · 9,394 accessesView PDFCite
Research ArticleOpen accessIn the abstractMissing Values Treatment and Feature Reduction Analysis to Enhance ClassificationD. Muralidharan, K. Renuka, Mulagala Jaswant et al.Datasets may have large number of features which makes it hard and time consuming to classify. Additionally, they may have irrelevant and noise features too with missing values. The missing values should be treated in a proper way so that the classifier accuracy can be improved. There is also a need to reduce features and select only the features necessary … …Journal of Computer Science, Vol. 16, Issue 2 · 20 Feb 2020 · 8,114 accessesView PDFCite
Research ArticleOpen accessIn the abstractUltimate Prediction of Stock Market Price MovementRebwar M. Nabi, Soran Ab. M. Saeed, Habibolah Bin Harron, Hamido FujitaInvestment in the stock market is currently very popular due to its economic gain. Numerous researchers’ and academicians’ work is focused on financial time series prediction due to its data availability and profitability. Therefore, this study presents the design and implementation of a novel binary classification framework to predict stock market trends. The framework is composed of data preprocessing, feature … …Journal of Computer Science, Vol. 15, Issue 12 · 25 Dec 2019 · 8,545 accessesView PDFCite
Research ArticleOpen accessIn the abstractDimensionality Reduction using Principal Component Analysis for Cancer Detection based on Microarray Data ClassificationAdiwijaya, Untari N. Wisesty, E. Lisnawati et al.Cancer is one of the most deadly diseases in the world. The International Agency for Research on Cancer (IARC) noted 14.1 million new cancer cases and 8.2 million deaths from cancer in 2012. In the last few years, DNA microarray technology has increasingly been used to analyze and diagnose cancer. Analysis of gene expression data in the form of microarray … …Journal of Computer Science, Vol. 14, Issue 11 · 15 Nov 2018 · 9,930 accessesView PDFCite
Research ArticleOpen accessIn the abstractUpdates on Nutritional Diversity in Sphenostylis stenocarpa (Hoechst ex. A. Rich.) Harms. for Food Security and ConservationCatherine Veronica Nnamani, Sunday Adesola Ajayi, Happiness Ogba Oselebe et al.Neglected and underutilized plant genetic resources constitute opportunity for diversification of food and environmental services globally, particularly within communities in developing country. They can provide, in some cases, higher nutrient content than traditional globally accepted staples commonly consumed. Currently, with climate uncertainty and the desire and challenge for sustainably produced food, there is an urgent need to promote crop diversity. … …American Journal of Agricultural and Biological Sciences, Vol. 13, Issue 1 · 10 Jul 2018 · 9,336 accessesView PDFCite
Research ArticleOpen accessIn the abstractFACIAL FEATURE EXTRACTION TECHNIQUES FOR FACE RECOGNITIONRahib H. AbiyevFace recognition is one of the biometric techniques used for identification of humans. The design of the face recognition system includes two basic steps. The first step is the extraction of the image's features and the second one is the classification of patterns. Feature extracting is a very important step in face recognition. The recognition rate of the system depends … …Journal of Computer Science, Vol. 10, Issue 12 · 23 Dec 2014 · 10,328 accessesView PDFCite
Research ArticleOpen accessIn the abstractHYPERPARAMETER 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 abstractDETECTION OF LAND USE AND LAND COVER CHANGES IN DIRAB REGION OF SAUDI ARABIA USING REMOTELY SENSED IMAGERIESR. Madugundu, K. A. Al-Gaadi, V. C. Patil, E. TolaKnowledge of Land Use and Land Cover (LULC) changes is important for many planning and management activities. It is thought to be an essential element for modeling and understanding the major land forms, especially in arid regions like Saudi Arabia. This study investigates the LULC changes in Dirab region of Saudi Arabia between 1980 and 2010, using Landsat TM/ETM+images. After … …American Journal of Environmental Sciences, Vol. 10, Issue 1 · 30 Jan 2014 · 8,013 accessesView PDFCite
Research ArticleOpen accessIn the abstractIMPROVED REAL-TIME FACE RECOGNITION BASED ON THREE LEVEL WAVELET DECOMPOSITION-PRINCIPAL COMPONENT ANALYSIS AND MAHALANOBIS DISTANCEEdy Winarno, Agus Harjoko, Aniati Murni Arymurthy, Edi WinarkoThe development of research in the field of real-time face recognition is a study that is being developed in the last decade. Face recognition is used to identify person from an image or video. Recognition rate and computation time of real-time face recognition is one of the big challenges that must be developed. This study proposes a model of face … …Journal of Computer Science, Vol. 10, Issue 5 · 17 Jan 2014 · 8,015 accessesView PDFCite
Research ArticleOpen accessIn the abstractFORECASTING THE FINANCIAL RETURNS FOR USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSISNop SopipanThe aim of this study was to forecast the returns for the Stock Exchange of Thailand (SET) Index by adding some explanatory variables and stationary Autoregressive order p (AR (p)) in the mean equation of returns. In addition, we used Principal Component Analysis (PCA) to remove possible complications caused by multicollinearity. Results showed that the multiple regressions based on PCA, … …Journal of Mathematics and Statistics, Vol. 9, Issue 1 · 17 Apr 2013 · 6,958 accessesView PDFCite