Results 81 to 90 of about 96,202 (258)
Solid Harmonic Wavelet Bispectrum for Image Analysis
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
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
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
Calibration of Ordinal Regression Networks
Recent studies have shown that deep neural networks are not well-calibrated and often produce over-confident predictions. The miscalibration issue primarily stems from using cross-entropy in classifications, which aims to align predicted softmax probabilities with one-hot labels.
Daehwan Kim, Haejun Chung, Ikbeom Jang
openaire +2 more sources
Pasta is a transcriptomic aging clock built on an age‐shift learning framework and trained on 17 000 samples across 21 datasets. It accurately predicts relative biological age across tissues, platforms, and species, captures stemness‐to‐senescence transitions, and identifies age‐modulatory perturbations.
Jérôme Salignon +6 more
wiley +1 more source
ENSEMBLE BAGGING WITH ORDINAL LOGISTIC REGRESSION TO CLASSIFY TODDLER NUTRITIONAL STATUS
One 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
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
Regression Models for Ordinal Data
Summary A general class of regression models for ordinal data is developed and discussed. These models utilize the ordinal nature of the data by describing various modes of stochastic ordering and this eliminates the need for assigning scores or otherwise assuming cardinality instead of ordinality.
openaire +2 more sources
Drivers of Precision Agriculture Adoption in Italian Viticulture
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
STUDENT SATISFACTION ANALYSIS WITH GENETIC ALGORITHM-BASED DATA AUGMENTATION AND REGRESSION MODELS [PDF]
Student satisfaction plays an important role in determining the quality, retention, and reputation of an institution. However, limited survey data can reduce the accuracy of predictive models.
P. Priyadarshini, K.T. Veeramanju
doaj +1 more source

