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116 results for “Feature selection”
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Research ArticleOpen accessPhrase in the titleIntegrated Clustering and Feature Selection Scheme for Text Documents.M. Thangamani, P. ThangarajProblem statement: Text documents are the unstructured databases that contain raw data collection. The clustering techniques are used group up the text documents with reference to its similarity. Approach: The feature selection techniques were used to improve the efficiency and accuracy of clustering process. The feature selection was done by eliminate the redundant and irrelevant items from the text document … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,163 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleSwarm-Based Feature Selection for Handwriting IdentificationSiti Zaiton Mohd Hashim, Khaled Mohammed Bin AbdlProblem statement: Handwriting identification is the study for identifying or verifying the writer of a given handwritten document. Since the handwriting features are the cornerstone in the writers' classification process, the classifier accuracy is sensitive in terms of how the writers are scored based on the used features. Approach: In this study, we introduced swarm intelligence as a features weighting … …Journal of Computer Science, Vol. 6, Issue 1 · 31 Jan 2010 · 7,403 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFrom Feature Selection to Building of Bayesian Classifiers: A Network Intrusion Detection PerspectiveKok-Chin Khor, Choo-Yee Ting, Somnuk-Phon AmnuaisukProblem statement: Implementing a single or multiple classifiers that involve a Bayesian Network (BN) is a rising research interest in network intrusion detection domain. Approach: However, little attention has been given to evaluate the performance of BN classifiers before they could be implemented in a real system. In this research, we proposed a novel approach to select important features by … …American Journal of Applied Sciences, Vol. 6, Issue 11 · 30 Nov 2009 · 7,072 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Novel Crow Search Optimization Based Feature Selection With Optimal DNN for Big Data ClassificationC. Mahesh, J. Ruby Elizabeth, S. Gnana Selvan et al.Big data analytics has become popular due to its applicability in various real-time applications. To attain better performance, big data can be analyzed using the machine learning and deep learning models at recent times, various domains have started to deal with big dataset which involves numerous sets of features. Repetitive and unwanted features, which reduces the classification performance can be … …Journal of Computer Science, Vol. 22, Issue 6 · 30 Jun 2026 · 1,244 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Metaheuristic-Optimized Feature Selection for Early-Stage Diabetes Prediction With SHAP-Guided Insight into Influential AttributesEsmay Azam Rochy, Jannatul Ferdaus, Uzzal Biswas et al.Diabetes is a metabolic disorder that causes elevated blood glucose. This long-term health condition can lead to cardiovascular diseases, stroke, kidney failure, visual impairment, neuropathy, and even death in critical cases. So, a Computer-Aided Diagnostic (CAD) system is necessary to diagnose diabetes automatically. A clinician can utilize a machine learning-based CAD system that automatically diagnoses many people. This paper will … …Journal of Computer Science, Vol. 22, Issue 2 · 24 Feb 2026 · 1,736 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePredicting Antigenic Peptides Using a Multi-Level Transformer Model with Enhanced Feature SelectionAshwini S., Minu R. I., Jeevan KumarThis Antigenic Peptide (APs) prediction is one of the most important roles to improve vaccine design and interpret immune responses. This paper develops a Multi-Level Pooling-based Transformer model, which improves the accuracy and efficiency of predicting T-cell epitopes. The model utilizes peptide sequences from the Immune Epitope Database, employing a refined Kolaskar and Tongaonkar algorithm for feature extraction and a … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,443 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleSentiment Analysis Using Light Weight - Gradient Boosting Machine based Feature SelectionBikku Ramavath, Srikanth Kadainti, Nemani SubashSentiment analysis is a significant task in Natural Language Processing (NLP) that differentiates the emotions and opinions expressed in text or reviews. The sentiment analysis is challenging due to the complex language patterns and inappropriate or redundant features used for classification. In this research, the Light Weight - Gradient Boosting Machine (LWGBM) based feature selection is proposed to choose relevant … …Journal of Computer Science, Vol. 21, Issue 5 · 26 May 2025 · 4,695 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDeep Learning-Based Approach for Identification of Potato Leaf Diseases Using Wrapper Feature Selection and Feature ConcatenationMuhammad Ahtsam Naeem, Muhammad Asim Saleem, Jarrar Amjad et al.The potato is a widely grown crop in many regions of the world. In recent decades, potato farming has gained incredible traction in the world. Potatoes are susceptible to several illnesses that stunt their development. This plant seems to have significant leaf disease. Early Blight and Late Blight are two prevalent leaf diseases that affect potato plants. The early detection … …Journal of Computer Science, Vol. 21, Issue 5 · 12 May 2025 · 5,171 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleClassification of Non-Small Cell Lung Cancer Based on Gene Expression in Cases of Smokers and Non-Smokers using Ensemble Methods with Statistical Based Feature SelectionFhira Nhita, Isman KurniawanLung cancer is one of the leading causes of death globally. One of the main risk factors for lung can ceris smoking, which causes more than 90% of lung cancer cases. There are two types of lung cancer, i.e., Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC), which the latter is the most common. One method that … …Journal of Computer Science, Vol. 18, Issue 10 · 30 Sep 2022 · 6,093 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleUsing Feature Selection as Accuracy Benchmarking in Clinical Data MiningJafreen Hossain, Nor FazlidaMohdSani, Aida Mustapha, Lilly SurianiAffendeyAutomated prediction of new patients’ disease diagnosis based on data mining analysis on historical data is proven to be an extremely useful tool in the medical innovation. There are several studies focusing on this particular aspect. The objective of this study is two-fold. First, we look into three different classifiers, which are the Naïve Bayes, Multilayer Perceptron (MLP) and Decision … …Journal of Computer Science, Vol. 9, Issue 7 · 20 Jun 2013 · 7,460 accessesView PDFCite