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280 results for “classification problem”
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Research ArticleOpen accessPhrase in the titleA Novel Ensemble Method for Regression via Classification ProblemsSami M. Halawani, Ibrahim A. Albidewi, Amir AhmadProblem statement: Regression via Classification (RvC) is a method in which a regression problem is converted into a classification problem. A discretization process is used to covert continuous target value to classes. The discretized data can be used with classifiers as a classification problem. Approach: In this study, we use a discretization method, Extreme Randomized Discretization (ERD), in which bin … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 7,383 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Derivative-Free Optimization Method for Solving Classification ProblemParvaneh Shabanzadeh, Malik Abu Hassan, Wah June LeongProblem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. There is a training set for each class. Those problems occur in a wide range of human activity. One of the most promising ways to data classification is based on … …Journal of Computer Science, Vol. 6, Issue 3 · 31 Mar 2010 · 7,505 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleImpact of an Extra Layer on the Stacking Algorithm for Classification ProblemsRodolfo Lorbieski, Silvia Modesto NassarClassifying and making decisions are tasks performed by any human being in their daily lives. Learning algorithms have been widely studied as tools to aid information management, with an objective to maximize the generalization capacity. Learning algorithms can be used individually or as a committee of machines (ensembles). An ensemble uses the solutions provided by several machines, making different combinations … …Journal of Computer Science, Vol. 14, Issue 5 · 10 Jan 2018 · 8,286 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleA 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 · 10,120 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleA Wide Scale Classification of Class Imbalance Problem and its Solutions: A Systematic Literature ReviewGillala Rekha, Amit Kumar Tyagi, V. Krishna ReddyIn today’s world, most of the data (real world) is present in imbalanced form by nature. This is because of not having efficient algorithms to put this data (i.e., generated data by billion of internet- connected devices (IoTs)) in respective format. Imbalanced data poses a great challenge to (both) data mining and machine learning algorithms. The imbalanced dataset consists of … …Journal of Computer Science, Vol. 15, Issue 7 · 3 Jul 2019 · 9,372 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleTowards Solving the Problem of Virtual Machine Placement in Cloud Computing: A Job Classification ApproachAuday Al-Dulaimy, Ahmed Zekri, Wassim Itani, Rached ZantoutCloud Computing is a paradigm that delivers services by providing an access to wide range of shared resources which are hosted in cloud data centers. One of the recent challenges in this paradigm is to enhance the energy efficiency in these data centers. In this study, a model that identifies common patterns for the jobs submitted to the cloud is … …Journal of Computer Science, Vol. 12, Issue 3 · 8 Apr 2016 · 7,283 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFlock Optimization Algorithm-Based Deep Learning Model for Diabetic Disease Detection ImprovementDivager Balasubramaniyan, Nor Azura Husin, Norwati Mustapha et al.Worldwide, 422 million people suffer from diabetic disease, and 1.5 million die yearly. Diabetes is a threat to people who still fail to cure or maintain it, so it is challenging to predict this disease accurately. The existing systems face data over-fitting issues, convergence problems, non-converging optimization complex predictions, and latent and predominant feature extraction. These issues affect the system's … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,208 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Laboratory Study of Bayesian Updating in Small Feedback-Based Decision ProblemsTakemi Fujikawa, Sobei H. OdaThis study explores small feedback-based decision problems experimentally. Conducted were the experiments in which the decision-maker’s payoff distribution was limited to either favorable distribution or unfavorable distribution. The first remarkable observation revealed complexity/loss aversion in the experiment. The second observation included the law of small numbers. Deviations from maximization were also observed. Finally, we investigated the imperfect Bayesian decision-makers observed … …American Journal of Applied Sciences, Vol. 2, Issue 7 · 31 Jul 2005 · 6,754 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Transformer Based Model to Detect Environmental Related Distress on Online Social MediaUtkarsh Sharma, Prateek Pandey, Shishir KumarOnline social media has been recently employed as the source of data for the detection of traffic-related activities and to control the flow of traffic in smart cities all over the world. Till now an ample amount of research work has been done in identification of traffic-related incidents with the help of online social media platforms (mostly Twitter). Along with … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 462 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 749 accessesView PDFCite