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Comparison of Gradient Boosting Decision Tree Algorithms for CPU Performance by Haithm Haithm, ALSHARI, Abdulrazak Yahya, Saleh, Alper, ODABAŞ

“…This paper aims to compare the performance of CPU implementation of the top three gradient boosting algorithms. We start by explaining how the three algorithms work and the hyperparameters similarities between them. …”
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Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

“…This work proposed the implementation of modified Artificial Bee Colony with Firefly algorithm for training the FLNN network to overcome the drawback of BP-learning algorithm. …”
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Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia by Hindia, Mhd Nour

“…Then, a multi criteria with two-threshold algorithm is proposed to prioritize the selection between the LTE and WiMAX as target technologies. …”
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Evaluating the performance of machine learning techniques in the classification of Wisconsin Breast Cancer by Obaid, Omar Ibrahim, Mohammed, Mazin Abed, Abd Ghani, Mohd Khanapi, A. Mostafa, Salama, AL-Dhief, Fahad Taha

“…Numerous research works have tried to apply the algorithms of machine learning for classifying breast cancer and it was proven by many researchers that machine learning algorithms act preferable in the diagnosing process. …”
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Identifying communities with modularity metric using Louvain and Leiden algorithms by Shibghatullah, Abdul Samad, Hairol Anuar, Siti Haryanti, Abal Abas, Zuraida, Md Yunos, Norhazwani, Setiad, Tedy, Mukhtar, Mohd Fariduddin

“…Performance comparisons between the two and their concept were summarised in detail, as well as the step-by-step learning process of the state-of-the-art algorithms. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

“…In one-side incomplete information problem, comparison between MGT algorithm and smart random trade-offs (SRT) algorithm indicates that MGT outperforms SRT. …”
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Age-based facial recognition using convoluted neural network deep learning algorithm by Julius Yong Wu Jien, Aslina Baharum, Shaliza Hayati A. Wahab, Nordin Saad, Muhammad Omar, Noorsidi Aizuddin Mat Noor

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Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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Operating a reservoir system based on the shark machine learning algorithm by Allawi M.F., Jaafar O., Mohamad Hamzah F., Ehteram M., Hossain M.S., El-Shafie A.

Multiobjective deep reinforcement learning for recommendation systems by Ee, Yeo Keat, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. …”
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Multi-objective deep reinforcement learning for recommendation systems by Keat, Ee Yeo, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. …”
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Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance by Alsariera Y.A., Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Ali N.

Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…In order to investigate the correlation between features and class, generated feature subsets are rearranged according to its mutual information. …”
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Operating a reservoir system based on the shark machine learning algorithm by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Ehteram, Mohammad, Hossain, Md Shabbir, El-Shafie, Ahmed

“…In the current study, the shark machine learning algorithm (SMLA) is proposed to develop an optimal rule for operating the reservoir. …”
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Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel by Mohammad Asaduzzaman , Rasel

“…Both phases of the research outputs are evaluated and compared with the state-of-the-art methods. The proposed algorithms that outperformed the state-of-the-art algorithms contributes to diagnosing early-stage Melanoma. …”
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Deep learning for face detection using matlab by Slim, Salim Adnan

“…High resolution for face detection was approximately 85%. The algorithm was able to distinguish between human and non-human faces. …”
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Adaptive Linear System Identification over Simulated Wireless Environment by Elamin, Musab Jabralla Omer Elamin

“…The work looks thoroughly on three forms of instantaneous learning algorithms which are: first order algorithms (e.g. least mean square (LMS)), second order algorithms (e.g. …”
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Usability prioritization using performance metrics and hierarchical agglomerative clustering in MAR-learning application by Cheng L.K., Selamat A., Mohamed Zabil M.H., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O.

Network analysis in a peer-to-peer energy trading model using blockchain and machine learning by Shukla, S., Hussain, S., Irshad, R.R., Alattab, A.A., Thakur, S., Breslin, J.G., Hassan, M.F., Abimannan, S., Husain, S., Jameel, S.M.

“…This will lead to profitable P2P energy trading between different distributed prosumers. By analyzing the simulation results of the proposed model and algorithm by benchmarking with the existing state-of-the-art techniques it's clear that the proposed algorithm shows marked improvement over network latency generated results. …”
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