Results 151 to 160 of about 24,738,021 (313)

Classification Trees for Problems with Monotonicity Constraints [PDF]

For classification problems with ordinal attributes very often theclass attribute should increase with each or some of theexplaining attributes. These are called classification problemswith monotonicity constraints. Classical decision tree algorithmssuch
Feelders, A.J., Potharst, R.
core   +1 more source

Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares

Behavior Research Methods, 2016
Cheng-Hsien Li
semanticscholar   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

A distance metric for ordinal data based on misclassification

Journal of Innovative Applied Mathematics and Computational Sciences
Distances between data sets are used for analyses such as classification and clustering analyses. Some existing distance metrics, such as the Manhattan (City Block or L1 ) distance, are suitable for use with categorical data, where the data subtype is ...
Dreas Nielsen
doaj   +1 more source

An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data.

Psychological methods, 2004
D. Flora, P. Curran
semanticscholar   +1 more source

Mental health service use among Filipino American and Korean American young adults during the COVID‐19 pandemic

American Journal of Community Psychology, EarlyView.
Abstract Despite the heightened mental health challenges amid rising Anti‐Asian sentiment, Asian Americans have significantly underutilized mental health services, a trend that persisted even before the COVID‐19 pandemic. Although considerable efforts have been made to understand how various factors are related to mental health service use in this ...
Michael Park, Eunseok Jeong, Nari Yoo, Yoonsun Choi, Leopoldo J. Cabassa, Miwa Yasui, David Takeuchi   +6 more
wiley   +1 more source

Associations between inclusive community coalition leadership and use of evidence‐based practices

American Journal of Community Psychology, EarlyView.
Abstract Community coalitions have the potential to elicit diverse participants' perspectives on complex issues and generate shared commitment to adaptive strategies. Ideally, these approaches have been found effective elsewhere. Despite evidence that leadership plays a generally important role in coalitions, there have been limited prior findings ...
Rebecca Wells, Nalini Ranjit, Louis D. Brown, Sarah M. Chilenski, Yvonne Mary Gaddy   +4 more
wiley   +1 more source

Ordinal Comparison of Multidimensional Deprivation: theory and application [PDF]

This paper develops an ordinal method of comparison of multidimensional inequality. In our model, population distribution g is more unequal than f when the distributions have common median and can be obtained from f by one or more shifts in population ...
Christoffer Sonne-Schmidt, Finn Tarp, Lars Peter Østerdal   +2 more
core  

Rapid Genome and Exome Sequencing in Inpatients: Clinical Impact at a Tertiary Academic Medical Center

American Journal of Medical Genetics Part A, EarlyView.
ABSTRACT The objective of this study is to describe outcomes of rapid exome (rES) and rapid genome sequencing (rGS) in an inpatient setting. This is a retrospective cohort of inpatients with rES or rGS during their hospitalization between April 2016 and November 2023.
Cecilia M. Kessler, Bryce A. Schuler, Elizabeth A. Jasper, Janet Talbert, Laura Duncan, Mackenzie Mosera   +5 more
wiley   +1 more source

Classification of Ordinal Data

, 2006
Classification of ordinal data is one of the most important tasks of relation learning. In this thesis a novel framework for ordered classes is proposed. The technique reduces the problem of classifying ordered classes to the standard two-class problem. The introduced method is then mapped into support vector machines and neural networks. Compared with
openaire   +2 more sources