9 results for “Ensemble Bag”

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Research ArticleOpen accessPhrase in the titlePerformance Analysis of LDA, AdaBoost and Ensemble Bag Classifiers for Automatically Recognizing Nine Common Facial ExpressionsM.D. Sumithra, M. Abdul RahimanFacial expression recognition holds a prominent role in today’s digital world with more Human –Computer Interaction happening in day to day life. Successful identification of facial expressions needs extraction of descriptive attributes from the active facial patches and accurate classification. This paper is presented with the comparison of three multi class classifiers namely Linear Discriminant Analysis, AdaBoost and Ensemble bag. … …Journal of Computer Science, Vol. 14, Issue 9 · 27 Sep 2018 · 7,791 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsSymbolic Aggregate approXimation-Local Binary Pattern Feature Descriptor Combination for Automatic Facial Expression RecognitionSumithra M.D., M. Abdul RahimanAutomatic identification of facial expression is a significant research area which is anticipated for real time processing in Human-Computer Interaction domain. Along with an efficient classifier for assigning the class label to each of the input face image, it is very necessary to have a strong feature vector for training the classifier. This paper proposes an effectual combination of Local … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 7,523 accessesView PDF Cite

Research ArticleOpen accessIn the abstractNonnegative Matrix Factorization Features Extraction and Ensemble Methods Classifier for ECG Image ClassificationHussain K. Ibrahim, Shawkat K. Guirguis, Hend A. ElsayedThis study is a novel proposed classification system for ECG image classification. This proposed system uses nonnegative matrix factorization for feature extraction and ensemble methods for classification, and the results are compared with the features extracted by the principal component analysis, kernel principal component analysis, and independent component analysis. Although algorithms find image classification challenging, humans typically find it easy. … …Journal of Computer Science, Vol. 21, Issue 4 · 15 Mar 2025 · 4,874 accessesView PDF Cite

Research ArticleOpen accessIn the abstractPM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive EvaluationShrabani Medhi, Minakshi GogoiAir pollution is a global issue. PM2.5 is considered to be the most dangerous pollutant. Prediction of PM2.5 concentration is important so that effective measures can be taken beforehand. A multitude of machine learning methodologies have been employed in forecasting PM2.5 levels, utilizing diverse combinations of ensemble classifiers and regressors. However, there are three important issues that need to be … …Journal of Computer Science, Vol. 20, Issue 9 · 20 Jun 2024 · 5,186 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEcological Function Evaluation of Soil and Water Conservation Measures for Power Transmission and Transformation Project Construction Based on Remote Sensing and it’s Improvement PathYang Han, Songsong Wang, Yanhui Yang et al.Assessing ecological functions is critical for determining the efficacy of soil and water conservation measures, especially during the development of power transmission and transformation projects. Efficient conservation practices are essential for reducing ecological effects and guaranteeing sustainable development. This research aims to create a resilient model, Ecological Function Prediction for Conservation Effectiveness (EFP-CE) that will classify conservation effectiveness as either … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 17 Mar 2025 · 7,737 accessesView PDF Cite

Review ArticleOpen accessIn the abstractA Survey of Methods for Managing the Classification and Solution of Data Imbalance ProblemKhan Md. Hasib, Md. Sadiq Iqbal, Faisal Muhammad Shah et al.The problem of class imbalance is extensive for focusing on numerous applications in the real world. In such a situation, nearly all of the examples are labeled as one class called majority class, while far fewer examples are labeled as the other class usually, the more important class is called minority. Over the last few years, several types of research … …Journal of Computer Science, Vol. 16, Issue 11 · 13 Nov 2020 · 10,129 accessesView PDF Cite

Research ArticleOpen accessIn the abstractBoosting-BoW Algorithm for Finding Kidney Diseases from Medical Test ReportsWisam A. Qader, Abbas M. AliThis paper introduces an approach to increase the accuracy rate of classification by employing Bag-of-Words (BoW) as a feature selection method along with machine learning algorithms to obtain a more accurate output. Because of its capability in quickly processing large sets of data and getting accurate results, this approach can be used in medical areas. Different ensemble approaches are generated … …Journal of Computer Science, Vol. 15, Issue 4 · 26 Apr 2019 · 7,504 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAdaptive Synthetic Oversampling Algorithm for Handling Class Imbalance in Multi-Class Data Stream ClassificationPriya S., Annie UthraConcept drift and class imbalanced data are major challenging processes involved in modern streaming data classification. Particularly, when integrated with difficult factors like the existence of noise, overlapping class distribution, concept drift, and data imbalance can considerably affect the classifier results. In addition, various challenges affect the performance of the existing oversampling schemes such as SMOTE and its derivatives. Regardless … …Journal of Computer Science, Vol. 18, Issue 7 · 26 Jul 2022 · 5,814 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEnhanced Ensemble Prediction Algorithms for Detecting Faulty Modules in Object Oriented Systems Using Quality MetricsM. Punithavalli, C. NeelamegamThe high usage of software system poses high quality demand from users, which results in increased software complexity. To address these complexities, software quality engineering methods should be updated accordingly and enhance their quality assuring methods. Fault prediction, a sub-task of SQE, is designed to solve this issue and provide a strategy to identify faulty parts of a program, so … …Journal of Computer Science, Vol. 8, Issue 12 · 20 Dec 2012 · 6,438 accessesView PDF Cite