A tutorial-based survey on feature selection: Recent advancements on feature selection
A Moslemi - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Curse of dimensionality is known as big challenges in data mining, pattern recognition,
computer vison and machine learning in recent years. Feature selection and feature …
computer vison and machine learning in recent years. Feature selection and feature …
A two-stage hybrid credit risk prediction model based on XGBoost and graph-based deep neural network
J Liu, S Zhang, H Fan - Expert Systems with Applications, 2022 - Elsevier
The credit risk prediction technique is an indispensable financial tool for measuring the
default probability of credit applicants. With the rapid development of machine learning and …
default probability of credit applicants. With the rapid development of machine learning and …
Decoding clinical biomarker space of COVID-19: Exploring matrix factorization-based feature selection methods
One of the most critical challenges in managing complex diseases like COVID-19 is to
establish an intelligent triage system that can optimize the clinical decision-making at the …
establish an intelligent triage system that can optimize the clinical decision-making at the …
[HTML][HTML] A novel explainable COVID-19 diagnosis method by integration of feature selection with random forest
Abstract Several Artificial Intelligence-based models have been developed for COVID-19
disease diagnosis. In spite of the promise of artificial intelligence, there are very few models …
disease diagnosis. In spite of the promise of artificial intelligence, there are very few models …
Flood monitoring by integration of Remote Sensing technique and Multi-Criteria Decision Making method
Traditional methodologies of flood monitoring are generally time-consuming and demanding
tasks. In most cases, there is no possibility of flood monitoring in large areas. Due to the …
tasks. In most cases, there is no possibility of flood monitoring in large areas. Due to the …
A novel granular ball computing-based fuzzy rough set for feature selection in label distribution learning
W Qian, F Xu, J Huang, J Qian - Knowledge-Based Systems, 2023 - Elsevier
Label distribution learning is a widely studied supervised learning diagram that can handle
the problem of label ambiguity. The increasing size of datasets is accompanied by the …
the problem of label ambiguity. The increasing size of datasets is accompanied by the …
Multi-attribute decision-making based on comprehensive hesitant fuzzy entropy
G ** an automated monitoring system for fast and accurate prediction of soil texture using an image-based deep learning network and machine vision system
To guarantee proper seedbed preparation, it is important to assess and control soil
aggregate size in tillage operations. Doing so would lead to higher crop yield and more …
aggregate size in tillage operations. Doing so would lead to higher crop yield and more …
Subspace learning for feature selection via rank revealing QR factorization: Fast feature selection
The identification of informative and distinguishing features from high-dimensional data has
gained significant attention in the field of machine learning. Recently, there has been …
gained significant attention in the field of machine learning. Recently, there has been …
Scour propagation rates around offshore pipelines exposed to currents by applying data-driven models
Offshore pipelines are occasionally exposed to scouring processes; detrimental impacts on
their safety are inevitable. The process of scouring propagation around offshore pipelines is …
their safety are inevitable. The process of scouring propagation around offshore pipelines is …