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Li-Na Wang, Hongxu Wei, Yuchen Zheng, Junyu Dong and Guoqiang Zhong
Ensemble learning, online learning and deep learning are very effective and versatile in a wide spectrum of problem domains, such as feature extraction, multi-class classification and retrieval. In this paper, combining the ideas of ensemble learning, on...
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Annwesha Banerjee Majumder, Somsubhra Gupta, Dharmpal Singh, Biswaranjan Acharya, Vassilis C. Gerogiannis, Andreas Kanavos and Panagiotis Pintelas
Heart disease is a leading global cause of mortality, demanding early detection for effective and timely medical intervention. In this study, we propose a machine learning-based model for early heart disease prediction. This model is trained on a dataset...
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Ahmed Alwakeel, Mohammed Alwakeel, Mohammad Hijji, Tausifa Jan Saleem and Syed Rameem Zahra
Image classification is one of the major data mining tasks in smart city applications. However, deploying classification models that have good generalization accuracy is highly crucial for reliable decision-making in such applications. One of the ways to...
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Panagiotis Filippakis, Stefanos Ougiaroglou and Georgios Evangelidis
Reducing the size of the training set, which involves replacing it with a condensed set, is a widely adopted practice to enhance the efficiency of instance-based classifiers while trying to maintain high classification accuracy. This objective can be ach...
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Ahmad Reda Alzighaibi
Currently, the primary concerns on the Internet are security and privacy, particularly in encrypted communications to prevent snooping and modification of Domain Name System (DNS) data by hackers who may attack using the HTTP protocol to gain illegal acc...
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