Spatial analysis of hyperspectral images for detecting adulteration levels in bon-sorkh (Allium jesdianum L.) seeds: Application of voting classifiers by Golshid Fathi, Seyed Ahmad Mireei, Mehrnoosh Jafari, Morteza Sadeghi, Hassan Karimmojeni, Majid Nazeri

“…Among the different feature selection methods, CARS-selected features performed best, with the corresponding voting model satisfactorily detecting adulteration levels, resulting in a RMSE of 6.69%. …”
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Improve the robustness of algorithm under adversarial environment by moving target defense by Kang HE, Yuefei ZHU, Long LIU, Bin LU, Bin LIU

“…Traditional machine learning models works in peace environment,assuming that training data and test data share the same distribution.However,the hypothesis does not hold in areas like malicious document detection.The enemy attacks the classification algorithm by modifying the test samples so that the well-constructed malicious samples can escape the detection by machine learning models.To improve the security of machine learning algorithms,moving target defense (MTD) based method was proposed to enhance the robustness.Experimental results show that the proposed method could effectively resist the evasion attack to detection algorithm by dynamic transformation in the stages of algorithm model,feature selection and result output.…”
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Bearing Defect Classification Algorithm Based on Autoencoder Neural Network by Manhuai Lu, Yuanxiang Mou

“…Comparative experiments show that the neural network can effectively complete feature selection and substantially improve classification accuracy while avoiding the laborious algorithm of the conventional method.…”
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A Convolutional Network-Based Intelligent Evaluation Algorithm for the Quality of Spoken English Pronunciation by Xia Zhan

“…Based on audio and convolutional neural network learning and training, it realizes the feature selection and classification recognition of spoken English pronunciation. …”
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Hierarchical micro-blog sentiment classification based on feature fusion by Xianying ZHU, Zhen LIU, Wei JIN, Tingting LIU, Cuijuan LIU, Yanjie CHAI

“…Sentiment classification is an important issue of opinion mining.It has a high application value to classify sentiment in micro-blogs.As traditional feature selection method has semantic gap,a neural network language model was used to propose a deep feature representation method based on probability model to distribute weight to the word vector.Using this method,text semantic vector could be built.In order to avoid the semantic gap,the deep features and shallow features of text were integrated and feature vector that contained semantic information was constructed.With SVM hierarchical classification model,a variety of sentiments could be classified.Experimental results show that the hierarchical sentiment classification method based on feature fusion can improve the accuracy of sentiment classification in micro-blogs.…”
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vmrseq: probabilistic modeling of single-cell methylation heterogeneity by Ning Shen, Keegan Korthauer

“…We present vmrseq, a statistical method that overcomes these challenges to detect VMRs with increased accuracy in synthetic benchmarks and improved feature selection in case studies. vmrseq also highlights context-dependent correlations between methylation and gene expression, supporting previous findings and facilitating novel hypotheses on epigenetic regulation. vmrseq is available at https://github.com/nshen7/vmrseq .…”
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Design of Super Resolution and Fuzzy Deep Learning Architecture for the Classification of Land Cover and Landsliding Using Aerial Remote Sensing Data by Junaid Ali Khan, Muhammad Attique Khan, Mohammed Al-Khalidi, Dina Abdulaziz AlHammadi, Areej Alasiry, Mehrez Marzougui, Yudong Zhang, Faheem Khan

“…The efficacy and stability of convolutional neural networks increase in image classification with the specified use of feature selection algorithm that causes remarkably improved decision making. …”
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Enhancing Pan evaporation predictions: Accuracy and uncertainty in hybrid machine learning models by Khabat Khosravi, Aitazaz A. Farooque, Amir Naghibi, Salim Heddam, Ahmad Sharafati, Javad Hatamiafkoueieh, Soroush Abolfathi

“…Notably, manually constructed input scenarios outperformed automated feature selection methods, with maximum temperature emerging as the most significant predictor of Ep variability. …”
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Model Klasifikasi Dengan Logistic Regression Dan Recursive Feature Elimination Pada Data Tidak Seimbang by Sutarman, Rimbun Siringoringo, Dedy Arisandi, Edi Kurniawan, Erna Budhiarti Nababan

“…The research results show that feature selection and class balancing have a positive impact. …”
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Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning by Hosna Tavakoli, Reza Rostami, Reza Shalbaf, Mohammad‐Reza Nazem‐Zadeh

“…This result was achieved by the k‐nearest neighbor algorithm, utilizing 12 brain neuroimaging features, selected by the feature selection method of minimum redundancy maximum relevance (MRMR). …”
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Two-stage Non-Intrusive Load Monitoring method for multi-state loads. by Lei Wang, Xia Han, Yushu Cheng, Jiaqi Ma, Xuerui Zhang, Xiaoqing Han

“…Then, load features with low redundancy is obtained through the Max-Relevance and Min-Redundancy (mRMR) feature selection algorithm from various operating states of loads that were not successfully classified. …”
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Evolutionary Approach for Relative Gene Expression Algorithms by Marcin Czajkowski, Marek Kretowski

“…As checking all possible subsets of genes is computationally infeasible, the RXA algorithms require feature selection and multiple restrictive assumptions. …”
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The Expanded Invasive Weed Optimization Metaheuristic for Solving Continuous and Discrete Optimization Problems by Henryk Josiński, Daniel Kostrzewa, Agnieszka Michalczuk, Adam Świtoński

“…The algorithm is evaluated by solving three well-known optimization problems: minimization of numerical functions, feature selection, and the Mona Lisa TSP Challenge as one of the instances of the traveling salesman problem. …”
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Tibetan Microblog Emotional Analysis Based on Sequential Model in Online Social Platforms by Lirong Qiu, Huili Zhang, Zhen Zhang, Qiumei Pu

“…In addition, our experimental results on the Sina Weibo dataset clearly demonstrate the effectiveness of feature selection and the efficiency of our classification method.…”
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Retinopathy Diabetic Recognition and Detection Using Novel Intelligent Algorithms by Liaquat Ali Rahoo

“…The proposed approach consists of four levels: pre-processing for noise removal and standardization of the input dataset, image segmentation using Spiking Neural Network (SNN) based on edge detection, dimension reduction and feature selection using percolation theory, and the final step of combining SNN and percolation theory for retinopathy area detection. …”
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Machine Learning Techniques for Classification of Stress Levels in Traffic by Amanda Trojan Fenerich, Egídio José Romanelli, Rodrigo Eduardo Catai, Maria Teresinha Arns Steiner

“… The aim of this study is to apply Machine Learning techniques for predicting and classifying the stress level of people commuting from home to work and also to evaluate the performance of prediction models using feature selection. The database was obtained through a structured questionnaire with 44 questions, applied to 196 people in the city of Curitiba, PR. …”
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Penyeimbangan Kelas SMOTE dan Seleksi Fitur Ensemble Filter pada Support Vector Machine untuk Klasifikasi Penyakit Liver by Muhammad Amir Nugraha, Muhammad Itqan Mazdadi, Andi Farmadi, Muliadi, Triando Hamonangan Saragih

“…The test can prove if SMOTE on class balancing and Ensemble Filter on feature selection can improve the classification performance of the SVM method.…”
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Approach for Text Classification Based on the Similarity Measurement between Normal Cloud Models by Jin Dai, Xin Liu

“…By the comparison among different text classifiers in different feature selection set, it fully proves that not only does CCJU-TC have a strong ability to adapt to the different text features, but also the classification performance is also better than the traditional classifiers.…”
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Fault Feature Analysis and Diagnosis Method of Rolling Bearing based on Empirical Mode Decomposition and Deep Belief Network by Yu Xiao, Fan Chunyang, Dong Fei, Ding Enjie, Wu Shoupeng, Wang Xin

“…Then,the extreme learning suite（ ELM） classifier feature selection method is proposed to remove the redundancy and interference characteristics of the original feature set and to select the fault state sensitive features. …”
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Revolutionizing colorectal cancer detection: A breakthrough in microbiome data analysis. by Mwenge Mulenga, Arutchelvan Rajamanikam, Suresh Kumar, Saharuddin Bin Muhammad, Subha Bhassu, Chandramathi Samudid, Aznul Qalid Md Sabri, Manjeevan Seera, Christopher Ifeanyi Eke

“…This paper introduces a novel feature engineering method that circumvents these limitations by amalgamating two feature sets derived from input data to generate a new dataset, which is then subjected to feature selection. This innovative approach markedly enhances the Area Under the Curve (AUC) performance of the Deep Neural Network (DNN) algorithm in colorectal cancer (CRC) detection using gut microbiome data, elevating it from 0.800 to 0.923. …”
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