Human Activity Recognition Based on the Hierarchical Feature Selection and Classification Framework by Yuhuang Zheng

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Relevant SMS Spam Feature Selection Using Wrapper Approach and XGBoost Algorithm by Diyari Jalal Mussa, Noor Ghazi M. Jameel

Subjects: “…SMS spam, wrapper methods, sequential feature selection, sequential forward selection, sequential backward selection, boosting classifier, extreme gradient boosting, XGBoost.…”
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Modified Particle Swarm Optimization on Feature Selection for Palm Leaf Disease Classification by Veri Julianto, Ahmad Rusadi Arrahimi, Oky Rahmanto, Mohammad Sofwat Aldi

“…This research focuses on modifying Particle Swarm Optimization (PSO) for feature selection in identifying diseases in palm oil leaves. …”
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Feature Selection and Machine Learning Approaches for Detecting Sarcopenia Through Predictive Modeling by Akhrorbek Tukhtaev, Dilmurod Turimov, Jiyoun Kim, Wooseong Kim

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Stochastic step-wise feature selection for Exponential Random Graph Models (ERGMs). by Helal El-Zaatari, Fei Yu, Michael R Kosorok

“…Addressing critical challenges such as ERGM degeneracy and computational complexity, our method integrates a systematic step-wise feature selection process. This approach effectively manages the intractable normalizing constants characteristic of ERGMs, ensuring the generation of accurate and non-degenerate network models. …”
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Sparse Linear Discriminant Analysis With Constant Between-Class Distance for Feature Selection by Shuangle Guo, Yongxia Li, Jianguang Zhang, Yue Liu, Tian Tian, Mengchen Guo

Subjects: “…Feature selection…”
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Steganographer identification of JPEG image based on feature selection and graph convolutional representation by Qianqian ZHANG, Yi ZHANG, Hao LI, Yuanyuan MA, Xiangyang LUO

“…Aiming at the problem that the feature dimension of JPEG image steganalysis is too high, which leads to the complexity of distance calculation between users and a decrease in the identification performance of the steganographer, a method for steganographer recognition based on feature selection and graph convolutional representation was proposed.Firstly, the steganalysis features of the user’s images were extracted, and the feature subset with highseparability was selected.Then, the users were represented as a graph, and the features of users were obtained by training the graph convolutional neural network.Finally, because inter-class separability and intra-class aggregation were considered, the features of users that could capture the differences between users were learned.For steganographers who use JPEG steganography, such as nsF5, UED, J-UNIWARD, and so on, to embed secret information in images, the proposed method can reduce the feature dimensions and computing.The identification accuracy of various payloads can reach more than 80.4%, and it has an obvious advantage at the low payload.…”
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Comparing Correlation-Based Feature Selection and Symmetrical Uncertainty for Student Dropout Prediction by Haryono Setiadi, Indah Paksi Larasati, Esti Suryani, Dewi Wisnu Wardani, Hasan Dwi Cahyono Wardani, Ardhi Wijayanto

Subjects: “…correlation-based feature selection…”
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Machine Learning- and Feature Selection-Enabled Framework for Accurate Crop Yield Prediction by Sandeep Gupta, Angelina Geetha, K. Sakthidasan Sankaran, Abu Sarwar Zamani, Mahyudin Ritonga, Roop Raj, Samrat Ray, Hussien Sobahi Mohammed

“…Crop information is collected in an experiment’s data set. Then, feature selection is performed using the Relief algorithm. …”
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A feature selection method based on instance learning and cooperative subset search by Xiaoyuan XU, Li HUANG

Subjects: “…feature selection…”
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Study on the Bearing Fault Diagnosis based on Feature Selection and Probabilistic Neural Network by Liu Yunzhe, Hu Jinhai, Ren Litong, Yao Kaixiang, Duan Jinfeng, Chen Lin

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Comparison of Feature Selection and Feature Extraction Role in Dimensionality Reduction of Big Data by Haidar Khalid Malik, Nashaat Jasim Al-Anber, Fuad AbdoEsmail Al- Mekhlafi

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Enhancing rice seed purity recognition accuracy based on optimal feature selection by Thi-Thu-Hong Phan, Le Huu Bao Nguyen

Subjects: “…Feature selection…”
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Feature selection in single-cell RNA sequencing data: a comprehensive evaluation by Petros Paplomatas, Konstantinos Lazaros, Georgios N. Dimitrakopoulos, Aristidis Vrahatis

“…We developed the GenesRanking package, which offers 20 techniques for dimensionality reduction, including filter-based and embedding machine learning–based methods. By integrating feature selection methods from both statistics and machine learning, we provide a robust framework for improving data interpretation. …”
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Feature selection algorithm based on improved particle swarm joint taboo search by Zhen ZHANG, Peng WEI, Yufeng LI, Julong LAN, Ping XU, Bo CHEN

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Advanced Feature Selection for Simplified Pattern Recognition within the Damage Identification Framework by G. Manson, R.J. Barthorpe

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Quantum-Based Feature Selection for Multiclassification Problem in Complex Systems with Edge Computing by Wenjie Liu, Junxiu Chen, Yuxiang Wang, Peipei Gao, Zhibin Lei, Xu Ma

“…The complex systems with edge computing require a huge amount of multifeature data to extract appropriate insights for their decision making, so it is important to find a feasible feature selection method to improve the computational efficiency and save the resource consumption. …”
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Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance by Romina Wild, Felix Wodaczek, Vittorio Del Tatto, Bingqing Cheng, Alessandro Laio

“…Abstract Feature selection is essential in the analysis of molecular systems and many other fields, but several uncertainties remain: What is the optimal number of features for a simplified, interpretable model that retains essential information? …”
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Improving Diabetes Prediction by Selecting Optimal K and Distance Measures in KNN Classifier by Emad Majeed Hameed, Hardik Joshi

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A feature selection and scoring scheme for dimensionality reduction in a machine learning task by PHILEMON UTEN EMMOH, christopher ifeanyi Eke, Timothy Moses

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