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13 results for “Weighted correlation”
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Research ArticleOpen accessEvery word in the titleA New Weighted Rank CorrelationTahani A. Maturi, Ezz H. AbdelfattahProblem Statement: There have been many cases in real life where two independent sources have ranked n objects, with the interest focused on agreement in the top rankings. Spearman's rho and Kendall's tau coefficients assigned equal weights to all rankings. As a result, the literature proposed several weighted correlation coefficients with emphasis on the top rankings, including the top-down, weighted … …Journal of Mathematics and Statistics, Vol. 4, Issue 4 · 31 Dec 2008 · 8,826 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSpiral Binomial and Related Distributions for Obsession to AbortionRamalingam ShanmugamRepeated abortion is considered an important health concern by the pregnant women and the governments. Educating the public about the impact of abortion becomes the government’s responsibility. For this purpose, the government agencies turn to health and medical researchers for opinion about the impact of abortion. The public health researchers turn to data for clues and seek pertinent data information … …International Journal of Research in Nursing, Vol. 3, Issue 2 · 13 Aug 2012 · 6,720 accessesView PDFCite
Research ArticleOpen accessIn the abstractEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 912 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 abstractThe Use of Band Selection in Weighted Linear Prediction for Hyperspectral Image ClassificationIbtissam Banit'ouagua, Mounir Ait Kerroum, Ahmed HammouchThe advancement of imaging procedures has made hyperspectral sensors fit for acquiring spectral data in many restricted and bordering bands, which brings about a high relationship between's neighboring bands and high information excess. It is important to decrease these bands previously advance analysis utilizing land cover classification and target location. Going for the classification undertaking, this paper displays another weighted … …Journal of Computer Science, Vol. 14, Issue 8 · 4 Sep 2018 · 8,262 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpline Estimator for Bi-Responses and Multi-Predictors Nonparametric Regression Model in Case of Longitudinal DataAdji Achmad Rinaldo Fernandes, I Nyoman Budiantara, Bambang Widjanarko Otok, SuhartonoNonparametric regression approach is used when the shape of the curve regression is unknown. The spline estimator approach for longitudinal data can accommodate the correlation between observations within the same subject, which is not found in the cross-section data, so that the autocorrelation assumption problem can be resolved. On the other hand, with bi-responses approach, it will accommodate any correlation … …Journal of Mathematics and Statistics, Vol. 11, Issue 2 · 8 Oct 2015 · 7,337 accessesView PDFCite
Research ArticleOpen accessIn the abstractMISSING DATA IMPUTATION USING WEIGHTED OF REGIME SWITCHING MEAN AND REGRESSIONJumlong Vongprasert, Bhusana PremanodeMissing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. The purpose of this work were first to develop the Weighted of Regime Switching Mean and Regression (WRSMRI) for missing data estimation and secondly to compare its efficiency of estimation and statistical power of a … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 3 May 2014 · 6,704 accessesView PDFCite
Research ArticleOpen accessIn the abstractEdge Sensing Demosaicing Using Adaptive Weighted InterpolationDev R. Newlin, Elwin Chandra MonieDemosaicing is a process of obtaining a full color image by interpolating the missing colors of an image captured from a digital still and video cameras that use a single-sensor array. The edges are not handled properly in the existing demosaicking methods. This study provides an effective demosaicing algorithm applying an adaptive weighted-edge interpolation to handle green pixels. Due to … …American Journal of Applied Sciences, Vol. 10, Issue 4 · 29 Apr 2013 · 6,960 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpline Estimator in Multi-Response Nonparametric Regression Model with Unequal Correlation of ErrorsBudi Lestari, I. Nyoman Budiantara, Sony Sunaryo, Muhammad MashuriProblem statement: In many applications two or more dependent variables are observed at several values of the independent variables, such as at time points. The statistical problems are to estimate functions that model their dependences on the independent variables and to investigate relationships between these functions. Nonparametric regression model, especially smoothing splines provide powerful tools to model the functions which … …Journal of Mathematics and Statistics, Vol. 6, Issue 3 · 30 Sep 2010 · 8,168 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Performance of Latent Root-M based RegressionHabshah Midi, Lau Ung HuaProblem statement: In the presence of multicollinearity, the estimation of parameters in multiple linear regression models by means of Ordinary Least Squares (OLS) is known to suffer severe distortion. An alternative approach was to use the modified OLS which was based on the latent roots and latent vectors of the correlation matrix of the independent and dependent variables. This procedure … …Journal of Mathematics and Statistics, Vol. 5, Issue 1 · 31 Mar 2009 · 8,654 accessesView PDFCite