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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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E-history Malaysian secondary school textbook using TF-IDF algorithm and text visualization / Nur Hafizah Mohd Ridzuan
Published 2020“…History is one of the school subjects in Malaysian schools and known as a compulsory subject that is required to pass the SPM examination. One of the main learning methods in Malaysian education is by using textbooks as it is a universal formal school learning material and a dominant resource of learning. …”
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Jogging activity recognition using k-NN algorithm
Published 2022“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Support directional shifting vector: A direction based machine learning classifier
Published 2021“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Published 2017“…Machine learning is being implemented in bioinformatics and computational biology to solve challenging problems emerged in the analysis and modeling of biological data such as DNA, RNA, and protein. …”
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2013“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…Multi-Verse Optimizer (MVO) is one of the most recent robust nature-inspired metaheuristic algorithm. It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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10
Feedforward neural network for solving particular fractional differential equations
Published 2024“…The second approach relies on Chelyshkov basis functions for approximation and utilizes the extreme machine learning algorithm for weight determination, achieving high accuracy and low computational time. …”
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11
A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Meta-heuristic algorithm has been successfully implemented on data clustering problems seeking a near optimal solution in terms of quality of the resultant clusters. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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Interpretation of machine learning model using medical record visual analytics
Published 2021“…This paper studied on the effectiveness of visual analytics techniques to identify the appropriate technique to be instantiated to the machine learning algorithm to further elaborate the results obtained by demonstrating transparency, interpreta- bility and explainability of the machine learning algorithm. …”
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Proceeding Paper -
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The final problem is the ability of the algorithm to solve large-scale problems, which mostly are the real world problems. …”
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15
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…This research focuses on the use of binaryencoded genetic algorithm (GA) to implement efficient search strategies for the optimal architecture and training parameters of a multilayer feed-forward ANN. …”
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Interpretation of machine learning model using medical record visual analytics
Published 2022“…This paper studied on the effectiveness of visual analytics techniques to identify the appropriate technique to be instantiated to the machine learning algorithm to further elaborate the results obtained by demonstrating transparency, interpretability and explainability of the machine learning algorithm. …”
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Proceeding Paper -
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Air pollution forecasting in Kuala Terengganu using Artificial Neural Network (ANN) / Nur Raudzah Abdullah
Published 2020“…Existing researches on air pollution forecasting used a variety of machine learning algorithm. One of the popular algorithms used to forecast the air pollution is Artificial Neural Network (ANN). …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The architecture provides a novel method to pattern recognition and is expected to be robust to any pattern recognition problem. …”
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A functional link neural network with modified cuckoo search for prediction tasks
Published 2017“…Neural network, especially the Multi-Layer Perceptron (MLP) which uses Back Propagation algorithm (BP) as a supervised learning method, has been successfully applied in various problems for meteorological prediction tasks. …”
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