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24 results for “categorical data”
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Research ArticleOpen accessPhrase in the titleHill Climbing Method Using Claus Model for Categorical DataB. OnoghojobiProblem statement: In this study, a locally unbiased test statistic based on the Claussian method was presented. Approach: In this respect, exploiting special structures of modified quadratic hill climbing method and the Claussian statistics were considered. Results: We derived a non-modified quadratic hill-climbing procedure. The performance of the model in testing the estimation of Latent data was shown. Conclusion/Recommendations: The … …Journal of Mathematics and Statistics, Vol. 5, Issue 4 · 31 Dec 2009 · 7,298 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleJoint Modelling of Longitudinal-Time-To-Event with Categorical Variable Indicators of Latent Classes: Application to Tuberculosis DataAdeboye Azeez, Mutambayi Ruffin, Ndege James, Qin YongsongIn many clinical and reliability research reports, the outcomes of basic interest is the time to a particular event happens in order to indicate the person’s “true” state of health or survival status. Different models have been used to analyze such data separately, but may be unsuitable if the longitudinal and health status measures are correlated. In this study, mixed … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 9 Jun 2020 · 6,686 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDetection of Aberrant Data Points for an effective Effort Estimation using an Enhanced Algorithm with Adaptive FeaturesS. Malathi, S. SridharProblem statement: The spiraling growth of IT industry has witnessed an unprecedented change in the software development paradigm, from algorithmic models to machine learning techniques. At present, there are no standard methods to predict the accuracy of software cost estimation, which is an important goal of the software community. Approach: This study proposes a simple and systematic algorithmic procedure for … …Journal of Computer Science, Vol. 8, Issue 2 · 21 Nov 2011 · 7,094 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Cluster Feature-Based Incremental Clustering Approach to Mixed DataA. M. Sowjanya, M. ShashiProblem statement: The main objective of this study is to develop an incremental clustering algorithm that can handle numerical as well as categorical attributes in a given dataset. The authors have previously reported a cluster feature-based algorithm, CFICA that can handle only numerical data. Appraoch: Since many of the real life data mining applications work with datasets that contain both … …Journal of Computer Science, Vol. 7, Issue 12 · 21 Oct 2011 · 7,159 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOrdinal Logistic Regression Model: An Application to Pregnancy OutcomesK. A. Adeleke, A. A. AdepojuProblem statement: This research aimed at modeling a categorical response i.e., pregnancy outcome in terms of some predictors, determines the goodness of fit as well as validity of the assumptions and selecting an appropriate and more parsimonious model thereby proffered useful suggestions and recommendations. Approach: An ordinal logistic regression model was used as a tool to model the three major … …Journal of Mathematics and Statistics, Vol. 6, Issue 3 · 30 Sep 2010 · 14,546 accessesView PDFCite
Research ArticleOpen accessIn the keywordsUtility Independent Privacy Preserving Data Mining on Vertically Partitioned DataE. Poovammal, M. PonnavaikkoProblem statement: Driven by mutual benefits, or by regulations that require certain data to be published, there has been a demand for the exchange and publication of data among various parties. Data publishing has been ubiquitous in many domains such as medical, business and education. Detailed person-specific data, present in the centralized server or in the distributed environment, in its … …Journal of Computer Science, Vol. 5, Issue 9 · 30 Sep 2009 · 6,835 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Effective Data Transformation Approach for Privacy Preserving ClusteringR. R. Rajalaxmi, A. M. NatarajanA new stream of research privacy preserving data mining emerged due to the recent advances in data mining, Internet and security technologies. Data sharing among organizations considered to be useful which offer mutual benefit for business growth. Preserving the privacy of shared data for clustering was considered as the most challenging problem. To overcome the problem, the data owner published … …Journal of Computer Science, Vol. 4, Issue 4 · 30 Apr 2008 · 7,112 accessesView PDFCite
Research ArticleOpen accessIn the keywordsToward a Good Decision to Improve the Weight of Control of Expenditure for Local CommunitiesAanouar Riad Solh, Mourad El BelkacemiIn order to improve the weight control of local government spending, we have developed a technique to supervise the classification of local authorities according to their expense ratios. This aims to develop the repository of rules and decision-making skills of business leaders of local communities and enabling to detect frauds in expenditure ratios that cause weakness of the Current Flow … …American Journal of Applied Sciences, Vol. 13, Issue 3 · 26 Mar 2016 · 6,992 accessesView PDFCite
Research ArticleOpen accessIn the abstractParameter-Expanded Data Augmentation for Analyzing Nominal Data With Missing Values Using Multinomial Probit ModelsSuwash Silwal, Xiao ZhangNominal data occur in many scientific fields, such as health-related studies, transportation, and econometrics. Due to the ubiquitousness of missing data, it is inevitable to analyze nominal data with missing values. As is well known, statistical methods for analyzing nominal variables are quite limited. The Multinomial Probit (MNP) model has been an essential tool for analyzing nominal categorical data, but … …Journal of Mathematics and Statistics, Vol. 22, Issue 1 · 23 May 2026 · 1,804 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