Combined Method for Informative Feature Selection for Speech Pathology Detection by D. S. Likhachov, M. I. Vashkevich, N. A. Petrovsky, E. S. Azarov

“…We propose to use LASSO (least absolute shrinkage and selection operator) and BSS (backward stepwise selection) methods together to select the most significant features for the detection of vocal pathologies, in particular amyotrophic lateral sclerosis. …”
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Angle Modulated Artificial Bee Colony Algorithms for Feature Selection by Gürcan Yavuz, Doğan Aydin

“…The objective of the feature subset selection is to eliminate the irrelevant and noisy feature in order to select optimum feature subsets and increase accuracy. …”
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The Utilization of Partial Least Squares for Simultaneous Feature Selection and Extraction by Elisavet Beki, Ntotsis Kimon

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Combination of Feature Selection and Learning Methods for IoT Data Fusion by V. Sattari-Naeini, Zahra Parizi-Nejad

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Multi-label feature selection based on dynamic graph Laplacian by Yonghao LI, Liang HU, Ping ZHANG, Wanfu GAO

Subjects: “…multi-label feature selection;dynamic graph Laplacian matrix;real-value label;classification…”
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Genetic feature selection algorithm as an efficient glioma grade classifier by Ting-Han Lin, Hung-Yi Lin

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Firefly Algorithm based Feature Selection for Arabic Text Classification by Souad Larabi Marie-Sainte, Nada Alalyani

“…It is commonly achieved after performing feature selection that consists of selecting appropriate features to enhance the classification accuracy. …”
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Explainability Feature Bands Adaptive Selection for Hyperspectral Image Classification by Jirui Liu, Jinhui Lan, Yiliang Zeng, Wei Luo, Zhixuan Zhuang, Jinlin Zou

“…The proposed feature band adaptive selection model focuses on the joint salient feature regions of the hyperspectral image, visualizes the feature contribution of the bands, more intuitively reveals the selection basis of the feature bands of the hyperspectral features in the process of deep learning, and selects the feature bands with high contribution to carry out classification experiments for verification. …”
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Deception detection based on micro-expression and feature selection methods by Shusen Yuan, Zilong Shao, Zhongjun Ma, Ting Cao, Hongbo Xing, Yong Liu, Yewen Cao

“…Two feature selection methods are applied to optimize these features. …”
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CUR matrix approximation through convex optimization for feature selection by Kathryn Linehan, Kathryn Linehan, Radu Balan

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FEATURE SELECTION COMPARATIVE PERFORMANCE FOR UNSUPERVISED LEARNING ON CATEGORICAL DATASET by Rachmad Fitriyanto, Mohamad Ardi

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Software Defect Prediction through Neural Network and Feature Selections by Mutasem Shabeb Alkhasawneh

“…To predict the software defect, this study proposed a model consisting of feature selection and classifications. The correlation base method was used for feature selection, and radial base function neural network (RBF) was used for classification. …”
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Prediction of Banks Efficiency Using Feature Selection Method: Comparison between Selected Machine Learning Models by Hamzeh F. Assous

“…Finally, we choose the best prediction model with the highest R2 in the training and the testing phases with/out feature selection that is the CHAID model. The best predictors of cost efficiency for Saudi banks are the capital ratios, namely, CAR total and CAR tier 1. …”
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Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

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A novel method for optimizing epilepsy detection features through multi-domain feature fusion and selection by Guanqing Kong, Guanqing Kong, Shuang Ma, Shuang Ma, Wei Zhao, Wei Zhao, Haifeng Wang, Haifeng Wang, Qingxi Fu, Qingxi Fu, Jiuru Wang

Subjects: “…feature selection…”
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DOA Estimation by Feature Extraction Based on Parallel Deep Neural Networks and MRMR Feature Selection Algorithm by Ashwaq Neaman Hassan Al-Tameemi, Mahmood Mohassel Feghhi, Behzad Mozaffari Tazehkand

“…It efficiently extracts spatial and temporal features, then fuses them and selects the distinct ones while removing the redundant ones. …”
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Support Vector Machine – Recursive Feature Elimination for Feature Selection on Multi-omics Lung Cancer Data by Nuraina Syaza Azman, Azurah A Samah, Ji Tong Lin, Hairudin Abdul Majid, Zuraini Ali Shah, Nies Hui Wen, Chan Weng Howe

“…Feature selection was performed on the LUSC multi-omics data using SVM-RFE to select several optimal feature subsets. …”
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A new representation in genetic programming with hybrid feature ranking criterion for high-dimensional feature selection by Jiayi Li, Fan Zhang, Jianbin Ma

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Optimal Feature Selection and Classification for Parkinson’s Disease Using Deep Learning and Dynamic Bag of Features Optimization by Aarti, Swathi Gowroju, Mst Ismat Ara Begum, A. S. M. Sanwar Hosen

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A multi-feature stock price prediction model based on multi-feature calculation, LASSO feature selection, and Ca-LSTM network by Xiao Chen, Lei Cao, Zhi Cao, HongWei Zhang

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