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Unsupervised strategies for naïve animals: New model of adaptive decision making inspired by baby chicks, turtles and insects

Precocial animals, the ones that move autonomously within hours after hatching or birth, have many biases they are born with ...
IEEE

Robust Semi-supervised Feature Selection with Multi-granularity Zentropy Modeling

Abstract: High-dimensional and weakly supervised (HiDWS) data present significant challenges for traditional machine learning and pattern recognition. Although semi-supervised feature selection has ...
IEEE

Unsupervised Feature Selection-Driven Active Learning for Semi-Supervised Automatic ECG Analysis

Abstract: Automatic analysis methods of electrocardiograms (ECGs) usually required large-scale annotated training data, but the annotation process is extremely time-consuming. While semi-supervised ...
Frontiers

Regional feature purification contrastive learning for wheat biotic stress detection

The identification of wheat infections has always been a considerable problem in agricultural forecasting. This paper presents an automated classification framework for wheat illnesses utilising ...
Frontiers

Advanced Supervised Machine Learning Techniques for Accurate Prediction of Diabetes Mellitus Using Feature Selection

The final, formatted version of the article will be published soon. Background): Diabetes Mellitus (DM) is a chronic metabolic disorder that poses a significant global health challenge, affecting ...
Scientific Research Publishing

Emmanuel, I., Sun, Y. and Wang, Z. (2024) A Machine Learning-Based Credit Risk Prediction Engine System Using a Stacked Classifier and a Filter-Based Feature Selection Method ...

ABSTRACT: Credit risk assessment plays an important role in financial services by estimating the chance of a borrower defaulting. Recently, although the Large Language Models (LLMs) have demonstrated ...