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285 articles for “Datasets”
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Review ArticleOpen accessIn the abstractA Systematic Literature Review of Software Defect Prediction Using Deep LearningAhmed Bahaa, Enas Mohamed Fathy, Ahmed Sharaf Eldin et al.The approaches associated with software defect prediction are used to reduce the time and cost of discovering software defects in source code and to improve the software quality in the organizations. There are two approaches to reveal the software defects in the source code. The first approach is concentrated on the traditional features such as lines of code, code complexity, … …Journal of Computer Science, Vol. 17, Issue 5 · 22 May 2021 · 10,967 accessesView PDFCite
Review ArticleOpen accessIn the abstractToward an Online DoS/DDoS Classification: An Empirical Study for Network Intrusion Detection SystemsTran Hoang Hai, Nguyen Trong Khiem, Nguyen Huu PhucIn recent years, Distributed Denial of Services (DDoS) attacks have caused significant losses to industry and government due to an increasing number of devices connected to the Internet. These devices use services-over-Internet more frequently with services characterized and provided seamlessly by 5G, Cloud and Edge Computing. According to Cisco Annual Internet Report, the frequency of DoS/DDoS attacks has increased more … …Journal of Computer Science, Vol. 17, Issue 3 · 30 Mar 2021 · 6,972 accessesView PDFCite
Research ArticleOpen accessIn the abstractDAD: A Detailed Arabic Dataset for Online Text Recognition and Writer Identification, a New TypeSaid S. SaloumThis paper presents a novel Arabic dataset that considers the characteristics of the Arabic language filling some gaps not covered by existing datasets. Conventional datasets consider Arabic in a similar way to Latin languages. These datasets either delete diacritic and supplement marks, considering them as defects, or keep them without considering the actual meaning. More than half of all Arabic … …Journal of Computer Science, Vol. 17, Issue 1 · 21 Jan 2021 · 7,859 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Techniques for Software Bug Prediction: A Systematic ReviewSyahana Nur’Ain Saharudin, Koh Tieng Wei, Kew Si NaThe goal of software bug prediction is to identify the software modules that will have the likelihood to get bugs by using some fundamental project resources before the real testing starts. Due to high cost in correcting the detected bugs, it is advisable to start predicting bugs at the early stage of development instead of at the testing phase. There … …Journal of Computer Science, Vol. 16, Issue 11 · 14 Nov 2020 · 9,377 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Approach of Texture Feature and Gradient Orientation for Computer Aided Diagnosis System Based on Breast Density ClassificationNujum Alabdulali, Alanod Bin Dris, Fatimah Alqahtani, Aseel Bin OthmanA Computer-Aided Diagnosis (CAD) system can perform an accurate diagnosis and help radiologists by presenting a second opinion about breast density. However, the development of a robust CAD system for breast density classification is still an open problem. In this study, we proposed a CAD system based on hybrid intelligent machine learning technique for automatic classification of breast density on … …Journal of Computer Science, Vol. 16, Issue 10 · 1 Nov 2020 · 6,759 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term MemoryThambusamy Velmurugan, Thiruvalluvan IndhumathyPredictive data analytics is a branch of data analytics where models are designed that effectively interpret; anticipate outcomes by analyzing present data to make predictions about future. One of the major attributes for prediction is time and there have been a considerable number of time series analytical models that are used for forecasting. Long Short-Term Memory (LSTM) is a deep … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 7,316 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Support Vector Machine based on Metaheuristic Search for Multiclass ProblemsAbdullah Saeed Ghareb, Mohammed Hamid Afif, Abdel-Rahman Hedar et al.Machine learning is an important field of artificial intelligent researches and it highly growing for real intelligent applications systems that relate brain computer interface to human brain activities. Support Vector Machine (SVM) is a popular machine learning approach, which can be used for pattern recognition, prediction and classification with many diverse applications. However, the SVM has many parameters, which have … …Journal of Computer Science, Vol. 16, Issue 7 · 9 Jul 2020 · 6,906 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of Probit and Logistic Regression Models in the Analysis of Dichotomous OutcomesAmrutha Jose, Mariyamma Philip, Lavanya Tumkur Prasanna, M. ManjulaProbit and logistic regression models are members of the family of generalized linear models, used for estimating the functional relationship between the dichotomous dependent and independent variables. The current study is designed to find the performance of logistic and probit regression models in different conditions under multivariate normality. The objective of the study is to compare the performance of probit … …Current Research in Biostatistics, Vol. 10, Issue 1 · 26 Mar 2020 · 17,036 accessesView PDFCite
Research ArticleOpen accessIn the abstractMissing Values Treatment and Feature Reduction Analysis to Enhance ClassificationD. Muralidharan, K. Renuka, Mulagala Jaswant et al.Datasets may have large number of features which makes it hard and time consuming to classify. Additionally, they may have irrelevant and noise features too with missing values. The missing values should be treated in a proper way so that the classifier accuracy can be improved. There is also a need to reduce features and select only the features necessary … …Journal of Computer Science, Vol. 16, Issue 2 · 20 Feb 2020 · 8,114 accessesView PDFCite
Research ArticleOpen accessIn the abstractFusion of Features and Extreme Learning Machine for Facial Expression RecognitionBayezid Islam, Arfat HossainHuman emotion is highly correlated to facial expressions. Due to its growing demand in different sectors, an emotion recognition method is proposed through recognizing facial expressions. The input image is preprocessed and then the resulting image is segmented into four facial expression regions following the newly proposed segmentation method. Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) are … …Journal of Computer Science, Vol. 15, Issue 12 · 28 Dec 2019 · 7,404 accessesView PDFCite