Ensemble Classification Model With CFS-IGWO–Based Feature Selection for Cancer Detection Using Microarray Data by Pinakshi Panda, Sukant Kishoro Bisoy, Sandeep Kautish, Reyaz Ahmad, Asma Irshad, Nadeem Sarwar

“…In this work, two ensemble techniques are proposed using majority voting technique and weighted average technique. Correlation feature selection (CFS) is used for feature selection, and improved grey wolf optimizer (IGWO) is used for feature optimization. …”
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Correction: Application of deep learning and feature selection technique on external root resorption identification on CBCT images by Nor Hidayah Reduwan, Azwatee Abdul Aziz, Roziana Mohd Razi, Erma Rahayu Mohd Faizal Abdullah, Seyed Matin Mazloom Nezhad, Meghna Gohain, Norliza Ibrahim

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Feature Selection and Classifier Parameters Estimation for EEG Signals Peak Detection Using Particle Swarm Optimization by Asrul Adam, Mohd Ibrahim Shapiai, Mohd Zaidi Mohd Tumari, Mohd Saberi Mohamad, Marizan Mubin

“…However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. …”
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Predicting Patients’ Revisit Intention Based on Satisfaction Scores: Combination of Penalized Regression and Neural Networks by Farshid Abdi, Shaghayegh Abolmakarem, Amir Karbassi Yazdi, Paul Leger, Yong Tan, Giuliani Coluccio

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Research on a multidimensional personalized recommendation model based on a situation and characteristics of the users by Chun-hua JU, Fu-guang BAO

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A novel group-based framework for nature-inspired optimization algorithms with adaptive movement behavior by Adam Robson, Kamlesh Mistry, Wai-Lok Woo

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Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification by Mustafa Serter Uzer, Nihat Yilmaz, Onur Inan

“…This paper offers a hybrid approach that uses the artificial bee colony (ABC) algorithm for feature selection and support vector machines for classification. …”
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Combination Hand-Crafted Features and Semi-Supervised Features Selection From Deep Features for Atrial Fibrillation Detection by Sara Mihandoost

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Rolling Bearing Fault Diagnosis Based on Domain Adaptation and Preferred Feature Selection under Variable Working Conditions by Xiao Yu, Wei Chen, Chuanlong Wu, Enjie Ding, Yuanyuan Tian, Haiwei Zuo, Fei Dong

“…Furthermore, preferred feature selection by fault sensitivity and feature correlation (PSFFC) is embedded into this framework for selecting features which are more beneficial to fault pattern recognition and reduce the redundancy of feature set. …”
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Systematic Framework to Predict Early-Stage Liver Carcinoma Using Hybrid of Feature Selection Techniques and Regression Techniques by Marium Mehmood, Nasser Alshammari, Saad Awadh Alanazi, Fahad Ahmad

“…In these techniques, we use feature selection methods to reduce the dataset’s feature, which include Filter, Wrapper, and Embedded methods. …”
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Kombinasi Feature Selection Fisher Score dan Principal Component Analysis (PCA) untuk Klasifikasi Cervix Dysplasia by Krisan Aprian Widagdo, Kusworo Adi, Rahmat Gernowo

“…In this work, combining feature selection Fisher Score (FScore) and Principal Component Analysis (PCA) is applied. …”
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ROLLING BEARING FAULT DIAGNOSIS BASED ON ADAPTIVE FEATURE SELECTION <italic>k</italic>-SUB CONVEX HULL by HU AiRu, WU ZhanTao, YANG Yu, CHENG JunSheng

“…An adaptive feature selection <italic>k</italic>-sub convex hull (AFSKCH) classificationmodel was proposed by combining feature selection and classifier optimization, which realized the integration of adaptive featureselection and classification. …”
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Improving the Accuracy of Early Detection of Parkinson's Disease Using Brain Signals Based on Feature Selection in Machine Learning by Shamimeh Sadat Nabavi Monfared, Mohammad Reza Yousefi

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Feature Selection in Cancer Classification: Utilizing Explainable Artificial Intelligence to Uncover Influential Genes in Machine Learning Models by Matheus Dalmolin, Karolayne S. Azevedo, Luísa C. de Souza, Caroline B. de Farias, Martina Lichtenfels, Marcelo A. C. Fernandes

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Towards the Development of a Cloud Computing Intrusion Detection Framework Using an Ensemble Hybrid Feature Selection Approach by Noah Oghenefego Ogwara, Krassie Petrova, Mee Loong Yang

“…It deploys a proposed new hybrid ensemble feature selection (FS) method. The ensemble includes FS algorithms of three different types (filter, wrapper, and embedded algorithms). …”
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A Novel Framework for Selecting Informative Meteorological Stations Using Monte Carlo Feature Selection (MCFS) Algorithm by Rizwan Niaz, Ibrahim M. Almanjahie, Zulfiqar Ali, Muhammad Faisal, Ijaz Hussain

“…In this paper, the Monte Carlo feature selection and interdependency discovery (MCFS-ID) algorithm-based framework is proposed to identify the important meteorological station in a particular region. …”
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<i>VFL-Cafe</i>: Communication-Efficient Vertical Federated Learning via Dynamic Caching and Feature Selection by Jiahui Zhou, Han Liang, Tian Wu, Xiaoxi Zhang, Yu Jiang, Chee Wei Tan

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Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method by Rencheng Fang, Tao Zhou, Baohua Yu, Zhigang Li, Long Ma, Tao Luo, Yongcai Zhang, Xinqi Liu

Subjects: “…feature selection…”
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Feature importance analysis for spammer detection in Sina Weibo by Yu-xiang ZHANG, Yu SUN, Jia-hai YANG, Da-lei ZHOU, Xiang-fei MENG, Chun-jing XIAO

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Prediction of High-ozone Events Using GAM, SMOTE, and Tail Dependence Approaches in Texas (2005–2019) by Benjamin Brown-Steiner, Xiong Zhou, Matthew J. Alvarado, Brook T. Russell

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