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12 results for “Unbalanced data”

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Research ArticleOpen accessPhrase in the titlePerformance Analysis of Garbage Classification Using Balanced and Unbalanced Dataset with EfficientNetV2B1 ArchitectureRetinderdeep Singh, Chander Prabha, Ayman Noor et al.This research concentrates on EfficientNetV2B1 deep learning model to classify garbage collection tasks, with both balanced and unbalanced dataset configurations. The dataset includes 7,260 images for the balanced dataset and 15,515 for the unbalanced one, both of the datasets are used to train and evaluate the model. Training and evaluation of the deep learning model with the standard performance variables: … …Journal of Computer Science, Vol. 20, Issue 10 · 27 Aug 2024 · 5,091 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOn Three-Way Unbalance Nested Analysis of VarianceSmaila S. Sanni, Eugene C. UkaegbuProblem statement: In this study, we give a simple analytically tractable procedure for solving three-way unbalanced nested Analysis of Variance (ANOVA). In many realistic situations, unbalanced design was unavoidable due to natural constraints and missing data. Approach: Here, we present a comprehensive approach for addressing solutions of problems arising from unbalanced nested ANOVA. We consider the F-statistics under the different … …Journal of Mathematics and Statistics, Vol. 8, Issue 1 · 10 Dec 2011 · 7,717 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwitter Sentiment Analysis Using Machine Learning and Deep Learning TechniquesSafa Khalid Al Sarayrah, Noor Mahmoud Alkudah, Hesham Yousef Al-kharabshehThis research investigates the use of Machine Learning (ML) and Deep Learning, including BiLSTM approaches, for Sentiment Analysis (SA) of consumer reviews on social media sites. Businesses are increasingly depending on online reviews to determine customer satisfaction due to social media's explosive growth. We used three classification models, the assessment of these attitudes uses Naive Bayes (NB), Support Vector Machine … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 6,813 accessesView PDFCite
Research ArticleOpen accessIn the abstractSparse Partial Optimal Transport via Quadratic RegularizationKhang Tran, Khoa Nguyen, Anh Nguyen et al.Partial Optimal Transport (POT) has recently emerged as a central tool in various Machine Learning (ML) applications. It lifts the stringent assumption of the conventional Optimal Transport (OT) that input measures are of equal masses, which is often not guaranteed in real-world datasets, and thus offers greater flexibility by permitting transport between unbalanced input measures. Nevertheless, existing major solvers for … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,905 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Analytics for Imbalanced DatasetMadhura Prabha R, Sasikala SThe primary issue in real-time big data classification is imbalanced datasets. Even though we have many balancing techniques to reduce imbalance ratio which is not suitable for big data that has scalability issues. This study is envisioned to explore different balancing techniques with experimental study. We tried comparing the effectiveness of various balancing strategies, including cutting-edge approaches for severely unbalanced … …Journal of Computer Science, Vol. 20, Issue 2 · 11 Jan 2024 · 5,473 accessesView PDFCite
Research ArticleOpen accessIn the abstractImprovement of Moroccan Dialect Sentiment Analysis Using Arabic BERT-Based ModelsGhizlane Bourahouat, Manar Abourezq, Najima DaoudiThis study addresses the crucial task of sentiment analysis in natural language processing, with a particular focus on Arabic, especially dialectal Arabic, which has been relatively understudied due to inherent challenges. Our approach centers on sentiment analysis in Moroccan Arabic, leveraging BERT models that are pre-trained in the Arabic language, namely AraBERT, QARIB, ALBERT, AraELECTRA, and CAMeLBERT. These models are … …Journal of Computer Science, Vol. 20, Issue 2 · 27 Dec 2023 · 6,545 accessesView PDFCite
Research ArticleOpen accessIn the abstractCombining SMOTE and OVA with Deep Learning and Ensemble Classifiers for Multiclass ImbalancedRattanawadee PanthongThe classification of real-world problems alwaysconsists of imbalanced and multiclass datasets. A dataset having unbalanced andmultiple classes will have an impact on the pattern of the classification modeland the classification accuracy, which will be decreased. Hence,oversampling method keeps the class of dataset balanced and avoids theoverfitting problem. The purposes of the study were to handle multiclassimbalanced datasets and to improve … …Journal of Computer Science, Vol. 18, Issue 8 · 23 Aug 2022 · 6,096 accessesView PDFCite
Case ReportOpen accessIn the abstractComputational Analysis of Environmental Risk ConditionersBarbara Carla Coelho Batista, João Victor Dutra Balboa, Caio Vincenzo Reis Dima et al.The intense urbanization process since the 1970s, coupled with the lack of adequate housing and social policies, has led large urban centers to disordered occupations and situations of geotechnical risk. These occupations were not implemented in a technically correct manner from the point of view of civil engineering, considering landscaping, drainage and paving, as well as edification. Areas at risk … …American Journal of Environmental Sciences, Vol. 16, Issue 5 · 16 Oct 2020 · 6,794 accessesView PDFCite
EditorialOpen accessIn the abstractRe-Paving the Road Built by Chemistry: A Challenge to Biochemistry and BiotechnologyAlberto A. IglesiasBiochemistry’s birth can be placed at the end of the nineteenth century, when Eduard Buchner made a clever interpretation of experimental observations on the generation of gas bubbles after addition (the original purpose was preservation) of sucrose to a yeast crude extract (Lagerkvist, 2005). Intelligently, Buchner concluded that the disaccharide had been fermented by broken cells’ suspension to produce CO2, … …American Journal of Biochemistry and Biotechnology, Vol. 11, Issue 1 · 26 Jan 2015 · 7,461 accessesView PDFCite
Research ArticleOpen accessIn the abstractToward a Hierarchical Bayesian Framework for Modelling the Effect of Regional Diversity on Household ExpenditurePudji Ismartini, Nur Iriawan, Setiawan, Brodjol Sutijo Supri UlamaProblem statement: Household expenditure analysis was highly demanding for government in order to formulate its policy. Since household data was viewed as hierarchical structure with household nested in its regional residence which varies inter region, the contextual welfare analysis was needed. This study proposed to develop a hierarchical model for estimating household expenditure in an attempt to measure the effect … …Journal of Mathematics and Statistics, Vol. 8, Issue 2 · 25 Jun 2012 · 7,304 accessesView PDFCite