Results 91 to 100 of about 109,915 (302)
lpfann/fri: Ordinal Regression
, 2018 <p>This release includes the support for ordinal regression (ordered classification) problems.</p ...
Boyuan Deng +6 more
core +1 more source
Advanced Science, EarlyView.Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang +2 more
wiley +1 more source
, 2014 Any multiple Criteria Decision Aiding (MCDA) method needs some preference parameters. The Decision Maker (DM) could be asked to provide directly all these parameters; however, because it needs a great cognitive effort, the indirect preference information is more used in practice. Starting from the indirect preference information, usually there could be
Corrente S +3 more
openaire +3 more sources
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT This study investigates the impact of geographical indication (GI) certification on the export performance of Turkish agri‐food products by analyzing both trade volume and unit value dynamics. Drawing on monthly data from 2000 to 2024 across 22 GI‐certified products, the research employs product‐level regressions, fixed‐effects panel models ...
Ihlas Sovbetov, Muge Burcu Ozdemir
wiley +1 more source
Ordinal regression Part 1: Introduction
, 2021 In this video, Dr Heini Väisänen introduces the method of ordinal regression and explains when to use it and what kind of variables are needed when used.
Väisänen, Heini
core
Drivers of Precision Agriculture Adoption in Italian Viticulture
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT This study examines the main drivers influencing the adoption of two types of precision farming technologies in the viticultural sector: Decision Support Systems (DSSs) and Variable Rate Technologies (VRTs). We apply a partial proportional odds model and find that socio‐demographic characteristics are not significant determinants of adoption ...
Olimpia Fontana +3 more
wiley +1 more source
ENSEMBLE BAGGING WITH ORDINAL LOGISTIC REGRESSION TO CLASSIFY TODDLER NUTRITIONAL STATUS
BarekengOne problem in classifying stunting data is that the data used does not have a balanced proportion. This study aims to apply the logistic regression classification method with ordinal scale response variables to overcome class imbalance through the ...
Luthfia Hanun Yuli Arini +3 more
doaj +1 more source
Farmers' Preferences for Gene Editing Crops and Influencing Factors
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT Gene editing (GE) is gaining momentum worldwide, but limited data on UK farmers' preferences hinders our understanding of its potential impact amid deregulation debates. Based on a survey of 200 English arable farmers, we employ a Latent Class Analysis and Multinomial Logit regressions to investigate current preferences for GE crops.
Bertolozzi‐Caredio Daniele +1 more
wiley +1 more source
Agribusiness, EarlyView.ABSTRACT This study investigates the financial literacy (FL) of Swedish farmers, its linkages to farmer characteristics, management accounting practices and farm outcomes by surveying Swedish Farm Accountancy Data Network farmers. Using item response theory, we expand the existing FL measurement specifically to the farming context, assess measurement ...
Uliana Gottlieb, Helena Hansson
wiley +1 more source
OSNR Monitoring Using Support Vector Ordinal Regression for Digital Coherent Receivers
IEEE Photonics Journal, 2019 An OSNR monitoring method assisted by support vector ordinal regression (SVOR) is proposed for digital coherent receivers. According to Godard's error of equalized signals obtained after polarization demultiplexing, the optical signal-to-noise ...
Ming Hao +6 more
doaj +1 more source