Privacy preservation in data intensive environment by Jyotir Moy Chatterjee, Raghvendra Kumar, Prasant Kumar Pattnaik, Vijender Kumar Solanki, Noor Zaman

“…In this article we have used feature selection for getting the best feature set to be selected for privacy preservation by using PCA (Principle Component Analysis). …”
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An optimized ensemble grey wolf-based pipeline for monkeypox diagnosis by Ahmed I. Saleh, Asmaa H. Rabie, Shimaa E. ElSayyad, Ali E. Takieldeen, Fahmi Khalifa

“…This study introduces a hybrid architecture for automatic monkeypox diagnosis by leveraging a modified grey wolf optimization model for effective feature selection and weighting. Additionally, the system uses an ensemble of classifiers, incorporating confusion based voting scheme to combine salient data features. …”
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Prediction of inhibitory peptides against E.coli with desired MIC value by Nisha Bajiya, Nishant Kumar, Gajendra P. S. Raghava

“…Subsequently, we employed machine learning regression models that integrated various features, including peptide composition, binary profiles and embeddings from large language models. Feature selection techniques, particularly mRMR, were utilized to refine our model inputs. …”
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Integrating Handcrafted Features with Machine Learning for Hate Speech Detection in Albanian Social Media by Fetahi Endrit, Hamiti Mentor, Susuri Arsim, Zenuni Xhemal, Ajdari Jaumin

“…To improve accuracy, we carefully performed feature selection to identify the most relevant features for detecting hate speech in the Albanian language. …”
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RGB-D salient object detection based on BC2 FNet network by WANG Feng, CHENG Yongmei

“…Secondly, a boundary-driven feature selection module is designed, which is dedicated to simultaneously focusing on important feature information and preserving boundary details in the process of RGB and depth modality fusion. …”
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An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning by S. M. Taslim Uddin Raju, Amlan Sarker, Apurba Das, Md. Milon Islam, Mabrook S. Al-Rakhami, Atif M. Al-Amri, Tasniah Mohiuddin, Fahad R. Albogamy

“…This paper aims to introduce a robust framework for forecasting demand, including data preprocessing, data transformation and standardization, feature selection, cross-validation, and regression ensemble framework. …”
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Rolling Bearing Fault Diagnosis Based on Sensitive Feature Transfer Learning and Local Maximum Margin Criterion under Variable Working Condition by Shiyuan Liu, Xiao Yu, Xu Qian, Fei Dong

“…Additionally, transferable sensitive feature selection by ReliefF and the sum of mean deviation (TSFSR) is proposed to reduce the redundant information of the original feature set, to select sensitive features for fault diagnosis, and to reduce the difference between the marginal distributions of the training and testing feature sets. …”
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Shifts in Bird Migration Timing in North American Long-Distance and Short-Distance Migrants Are Associated with Climate Change by Jay Zaifman, Daoyang Shan, Ahmet Ay, Ana Gabriela Jimenez

“…Furthermore, we performed feature selection to determine important factors for changing migration timing of birds. …”
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Application of Radiomics Model of CT Images in the Identification of Ureteral Calculus and Phlebolith by Qiuyue Yu, Jiaqi Liu, Huashan Lin, Pinggui Lei, Bing Fan

“…Then, the maximum correlation minimum redundancy criterion and the least absolute shrinkage and selection operator algorithm were used for texture feature selection. The feature subset with the most predictability was selected to establish the 3D radiomics model. …”
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Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion by Ying Chen, Yuanning Liu, Xiaodong Zhu, Fei He, Hongye Wang, Ning Deng

“…In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. …”
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Orthogonal Capsule Network with Meta-Reinforcement Learning for Small Sample Hyperspectral Image Classification by Prince Yaw Owusu Amoako, Guo Cao, Boshan Shi, Di Yang, Benedict Boakye Acka

“…The OCN-MRL framework employs Meta-RL for feature selection and CapsNet for classification with a small data sample. …”
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Efficient and accurate determination of the degree of substitution of cellulose acetate using ATR-FTIR spectroscopy and machine learning by Frank Rhein, Timo Sehn, Michael A. R. Meier

“…By applying a n-best feature selection algorithm based on the F-statistic of the Pearson correlation coefficient, several relevant areas were identified and the optimized model achieved an improved MAE of 0.052. …”
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A Lightweight Network with Domain Adaptation for Motor Imagery Recognition by Xinmin Ding, Zenghui Zhang, Kun Wang, Xiaolin Xiao, Minpeng Xu

“…Additionally, lightweight experiments were conducted from two perspectives: model structure optimization and data feature selection. The results demonstrated the potential advantages of this method for practical applications in motor imagery recognition systems.…”
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Improving wheat yield prediction through variable selection using Support Vector Regression, Random Forest, and Extreme Gradient Boosting by Juan Carlos Moreno Sánchez, Héctor Gabriel Acosta Mesa, Adrián Trueba Espinosa, Sergio Ruiz Castilla, Farid García Lamont

“…Using clustering, feature selection, and variable combination techniques, particularly agronomic variables such as harvest index (HI) and biomass (BM), provided complementary information to the Normalized Difference Vegetation Index (NDVI). …”
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Enhancing Stock Portfolio Selection with Trapezoidal Bipolar Fuzzy VIKOR Technique with Boruta-GA Hybrid Optimization Model: A Multicriteria Decision-Making Approach by Sunil Kumar Sharma

“…The Boruta-GA approach combines the advantages of the Genetic Algorithm (GA) and Boruta Optimization Algorithm (BOA) methods, implementing the comprehensive feature selection capability of Boruta to detect all relevant features and harnessing the strength of GA to bring about improvement within a wide range of datasets. …”
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Hybrid deep learning approach for brain tumor classification using EfficientNetB0 and novel quantum genetic algorithm by Kerem Gencer, Gülcan Gencer

“…It is aimed to develop the feature selection method. With this hybrid method, high reliability and accuracy in brain tumor classification was achieved. …”
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A Comprehensive Review of Wind Power Prediction Based on Machine Learning: Models, Applications, and Challenges by Zongxu Liu, Hui Guo, Yingshuai Zhang, Zongliang Zuo

“…The review also explores critical aspects such as data preprocessing, feature selection strategies, and model optimization techniques, which significantly enhance prediction accuracy and robustness. …”
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Deep learning-based differential gut flora for prediction of Parkinson's. by Bo Yu, Hang Zhang, Min Zhang

“…Subsequently, a preprocessing method called CRFS (combined ranking using random forest scores and principal component analysis contributions) was introduced for feature selection. Following this, the proposed LSIM (LSTM-penultimate to SVM Input Method) approach was utilized for classifying Parkinson's patients. …”
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Optimized Novel Text Embedding Approach for Fake News Detection on Twitter X: Integrating Social Context, Temporal Dynamics, and Enhanced Interpretability by Mahmoud AlJamal, Rabee Alquran, Ayoub Alsarhan, Mohammad Aljaidi, Wafa’ Q. Al-Jamal, Ali Fayez Alkoradees

“…Leveraging the CIC Truth Seeker Dataset 2023, we applied SHAP for feature selection and interpretability, ensuring transparency in the model’s predictions. …”
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Automatic Segmentation of Ischemic Stroke Lesions in CT Perfusion Maps Using Deep Learning Networks by Lida Zare Lahijan, Saeed Meshgini, Reza Afrouzian

“…The proposed network architecture includes the 7 Graph Convolutional layer, which can automatically perform feature selection/extraction and classify the resulting feature vector. …”
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