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

“…Gradient Boosting Decision Trees (GBDT) algorithms have been proven to be among the best algorithms in machine learning. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

“…To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. …”
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Optimizing the travel distance between mosque and muslim affair activities using Delaunay Triangulation / Siti Nor Dalila Shamsul Bahar by Shamsul Bahar, Siti Nor Dalila

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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

“…Multiple deep-learning models are proposed for segmentation. Several imaging, computer vision, and pattern recognition algorithms are employed to describe five dermoscopic features. …”
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AR oriented pose matching mechanism from motion capture data by Iqbal J., Sidhu M.S., Ariff M.B.M.

“…This proposed algorithm is compared with other published methods in terms of frame level accuracy and learning time of dance session. …”

High Accuracy Estimation Of Head Yaw Using Bounding Box Algorithm On A Vision Based System by Tarmizi, Aine Ilina

“…The objectives of the research are divided into three, to detect a face from the real-time stream of a camera and obtain bounding box coordinates around the detected face of the human, to analyze the change of distance and head yaw angle between the human face and camera with the effect of area and width of the bounding box on and lastly to design and validate the algorithm for estimation of the head yaw angle from the viewpoint of the camera. …”
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An improved directed random walk framework for cancer classification using gene expression data by Seah, Choon Sen

“…Sub-algorithms of SDW can be further divided into data pre-processing phase, specific tuning parameter selection, weight as additional variable, and exclusion of unwanted adjacency matrix. …”
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Analysis of Sentiment Based on Opinions from the 2019 Presidential Election by Nurul Adha Oktarini, Saputri, Misinem, ., Khoirul, Zuhri

“…The Naive Bayes Classifier algorithm was employed to classify the tweet data. …”
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K-Means Clustering Approach for Intelligent Customer Segmentation Using Customer Purchase Behavior Data by Kayalvily, Tabianan, Shubashini, Velu, VInayakumar, Ravi

“…In order to process the collected data and segment the customers, an learning algorithm is used which is known as K-Means clustering. …”
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Temporal integration based factorization to improve prediction accuracy of collaborative filtering by Al-Qasem, Al-Hadi Ismail Ahmed

“…The data sparsity problem has been solved by several approaches such as Bayesian probabilistic, machine learning, genetic algorithm, particle swarm optimization and matrix factorization. …”
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Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi by Hayder Faeq Rasool , Alhashimi

“…Finally, a State-Action-Reward-State-Action (SARSA) algorithm, which is a reinforcement learning approach, is proposed to solve the power allocation optimization problem. …”
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Security alert framework using dynamic tweet-based features for phishing detection on twitter by Liew, Seow Wooi

“…The challenging differences between the phishing attacks on email and Twitter are that Twitter disseminates vast information and is difficult to be detected unlike email. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

“…Most of the applied approaches are based on single task learning (STL) using machine learning algorithms, such as Logistic Regression (LR) and Hierarchical Classifier (HC) based on the divide-and-conquer approach. …”
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The comparison of interactive 3D visualization between static and animated approaches for learning binary tree topic / Mohd Zulhisam Yaakub by Yaakub, Mohd Zulhisam

“…However, the research has not consistently considered instructional approaches for learning algorithm lesson, and some researches indicated that utilized methods might not be enough. …”
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Walking gait event detection based on electromyography signals using artificial neural network by Nazmi, Nurhazimah, Abdul Rahman, Mohd Azizi, Yamamoto, Shin Ichiroh, Ahmad, Siti Anom

“…The mean absolute different values between artificial neural network and footswitch data for learned data were 16 ± 18 ms and 21 ± 18 ms for heel strike and toe off, respectively. …”
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Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device by Shanmuga, Pillai A/L Murutha Muthu

“…SAX algorithm changes the original time series data into a symbolic string and perform the discretization by dividing a time series into equal-sized segments. …”
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End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels by Mfarej, Sumaya Dhari Awad

“…In the fourth part a deep learning (DL) algorithm of channel estimation for two fad�ing channel models, Tropical and Temperate in the satellite communication system is presented. …”
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Cognitive knowledge-based model for adaptive feedback: A case in physics / Andrew Thomas Bimba by Andrew Thomas, Bimba

“…Tailoring feedback according to student’s characteristics and other external parameters is a promising way to implement adaptation in computer-based learning environment. There is an increase in the implementation of adaptive feedback models, which focus on the relationship between adaptive feedback and learning gains. …”
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A lightweight graph-based pattern recognition scheme in mobile ad hoc networks. by Raja Mahmood, Raja Azlina, Muhamad Amin, Anang Hudaya, Amir, Amiza, Khan, Asad I.

“…The comparison study between DGHN and the iterative, highly computational self organizing map (SOM) is also reviewed. …”
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Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction by Shoorangiz, Mohammadreza

“…The development sequence of such method can be divided into two parts: Developing network structure to employ complex fuzzy logic and proposing learning algorithm to train the system. …”
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