Results 31 to 40 of about 1,793,545 (266)
Change detection in categorical evolving data streams [PDF]
, 2014 Detecting change in evolving data streams is a central issue for accurate adaptive learning. In real world applications, data streams have categorical features, and changes induced in the data distribution of these categorical features have not been ...
Aggarwal C. C. +4 more
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A Novel Price Prediction Service for E-Commerce Categorical Data
Mathematics, 2023 Most e-commerce data include items that belong to different categories, e.g., product types on Amazon and eBay. The accurate prediction of an item’s price on an e-commerce platform will facilitate the maximization of economic benefits for the seller and ...
Ahmed Fathalla, Ahmad Salah, Ahmed Ali
doaj +1 more source
MCMC for Imbalanced Categorical Data
, 2017 Many modern applications collect highly imbalanced categorical data, with some categories relatively rare. Bayesian hierarchical models combat data sparsity by borrowing information, while also quantifying uncertainty.
Dunson, David B. +3 more
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Missing value imputation Techniques: A Survey
UHD Journal of Science and Technology, 2023 Numerous of information is being accumulated and placed away every day. Big quantity of misplaced areas in a dataset might be a large problem confronted through analysts due to the fact it could cause numerous issues in quantitative investigates.
Wafaa Mustafa Hameed, Nzar A. Ali
doaj +1 more source
Communication and Language Profiles of Children Treated for Posterior Fossa Brain Tumors
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Cognitive and language deficits are frequently reported sequelae of posterior fossa brain tumors (PFBT). Typically, delayed onset impedes prompt assessment and early intervention. This has devastating implications for quality of life.
Zara Sved +4 more
wiley +1 more source
Qualitative - Binary, Nominal and Ordinal Data Analysis in Medical Science
National Journal of Community Medicine, 2022 The outcome of any medical research is belonged to the human beings. The correct application of statistical test has its paramount importance. This article provides the details of categorical data analysis test with example and with its interpretation ...
Swati Patel
doaj +1 more source
ProbCD: enrichment analysis accounting for categorization uncertainty [PDF]
, 2007 As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or ...
A Lewin +22 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Characterizing stressful events reported by childhood cancer survivors experienced throughout the lifespan may help improve trauma‐informed care relevant to the survivor experience. Methods Participants included 2552 survivors (54% female; 34 years of age) and 469 community controls (62% female; 33 years of age) from the St.
Megan E. Ware +13 more
wiley +1 more source
Categorical linkage‐data analysis
Statistics in MedicineAnalysis of integrated data often requires record linkage in order to join together the data residing in separate sources. In case linkage errors cannot be avoided, due to the lack a unique identity key that can be used to link the records unequivocally, standard statistical techniques may produce misleading inference if the linked data are treated as ...
Li‐Chun Zhang, Tiziana Tuoto
openaire +2 more sources
Clustering and variable selection for categorical multivariate data [PDF]
, 2013 This article investigates unsupervised classification techniques for categorical multivariate data. The study employs multivariate multinomial mixture modeling, which is a type of model particularly applicable to multilocus genotypic data.
Bontemps, Dominique, Toussile, Wilson
core +5 more sources