Results 41 to 50 of about 96,053 (159)
Feature Relevance Bounds for Ordinal Regression [PDF]
CoRR, 2019 The increasing occurrence of ordinal data, mainly sociodemographic, led to a renewed research interest in ordinal regression, i.e. the prediction of ordered classes. Besides model accuracy, the interpretation of these models itself is of high relevance, and existing approaches therefore enforce e.g. model sparsity.
Pfannschmidt, Lukas +5 more
openaire +4 more sources
Exploiting Structured Global and Neighbor Orders for Enhanced Ordinal Regression
InformationOrdinal regression combines classification and regression techniques, constrained by the intrinsic order among categories. It has wide-ranging applications in real-world scenarios, such as product quality grading, medical diagnoses, and facial age ...
Imam Mustafa Kamal +4 more
doaj +1 more source
The Scientific World Journal, 2022 Background. Socioeconomic status (SES) refers to an individual’s or group’s social position or class, which is often determined by a combination of education, income, and occupation.
Mesfin Esayas Lelisho +2 more
doaj +1 more source
Asian Nursing Research, 2020 Summary: Purpose: The purpose of this study was to identify the factors affecting the satisfaction with patient-controlled analgesia (PCA) of patients using a generalized ordinal logistic regression model and to evaluate the difference in results of the
Wonhee Baek +3 more
doaj +1 more source
Ordinal Regression as Structured Classification
CoRR, 2019 This paper extends the class of ordinal regression models with a structured interpretation of the problem by applying a novel treatment of encoded labels. The net effect of this is to transform the underlying problem from an ordinal regression task to a (structured) classification task which we solve with conditional random fields, thereby achieving a ...
Niall Twomey +3 more
openaire +2 more sources
Some Properties of a Recently Introduced Approach to Ordinal Regression
Austrian Journal of Statistics, 2016 The statistical properties of a novel approach to ordinal regression which was only recently introduced in the literature are discussed. It is shown that for ordinal explanatory variables the approach is equivalent to isotonic regression, with some ...
Florian Frommlet
doaj +1 more source
Peningkatan Ketepatan Klasifikasi dengan Metode Bootstrap Aggregating pada Regresi Logistik Ordinal
Intensif: Jurnal Ilmiah Penelitian Teknologi dan Penerapan Sistem Informasi, 2019 Baby's birth weight is influenced by characteristics of pregnant women such as age, parity, education level, pregnancy visit, and gestational age. Classification of the birth weight of a baby is grouped into several groups, namely low birth weight ...
I Ketut Putu Suniantara +2 more
doaj +1 more source
Incremental sparse Bayesian ordinal regression
Neural Networks, 2018 Ordinal Regression (OR) aims to model the ordering information between different data categories, which is a crucial topic in multi-label learning. An important class of approaches to OR models the problem as a linear combination of basis functions that map features to a high dimensional non-linear space.
Chang Li 0003, Maarten de Rijke
openaire +6 more sources
IDENTIFIKASI KARAKTERISTIK KORBAN KECELAKAAN LALU LINTAS DI SIDOARJO TAHUN 2016
The Indonesian Journal of Public Health, 2019 Traffic accident becomes a very serious case because it causes not only material loss but also physical and psychological harms to the subject and the people around him. Accidents that occurred resulted in not only injuries but also death.
daniar mukti septianingtyas
doaj +1 more source
Multimodal multi-output ordinal regression for discovering gravitationally-lensed transients
Machine Learning: Science and TechnologyGravitational lenses are caused by massive astronomical objects that distort space-time, bending light. They can distort transient astrophysical events, such as supernovae (SN), which are the subject of extensive study.
Nicolò Oreste Pinciroli Vago +1 more
doaj +1 more source