Search Results - (( data visualisation a algorithm ) OR ( parameter optimization mining algorithm ))
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Tree-based contrast subspace mining method
Published 2020“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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Accelerated mine blast algorithm for ANFIS training for solving classification problems
Published 2016“…Mine Blast Algorithm (MBA) is newly developed metaheuristic technique. …”
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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength
Published 2015“…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
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Multi-dimensional Data Visualisation using Mobile Augmented Reality
Published 2020“…Therefore, this algorithm uses AR to provide a multi-display solution for improved data visualisation after processing, summarising and classifying data. …”
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Effectiveness of silhouette rendering algorithms in terrain visualisation
Published 2002“…This approach has been implemented in a 3D modelling system to create a new method of displaying and viewing terrain data in an artistic style. …”
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Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…This criterion is responsible for adding only the important terms to each rule, thus discarding noisy data. The ACS algorithm is designed to optimize the IR parameter during the learning process of the Ant-Miner algorithm. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…The SVM is a one technique of machine learning techniques that is well known technique, learning with supervised and have been applied perfectly to a vary problems of: regression, classification, and clustering in diverse domains such as gene expression, web text mining. In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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Visualisation System of COVID-19 Data in Malaysia
Published 2021“…This study aims to provide a system, using COVID-19 data as a sample to visualise and analyse cases, deaths, discharged ICU cases updates in Malaysia as a whole state wise of COVID-19 daily statistics. …”
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3D terrain visualisation for GIS: A comparison of different techniques
Published 2011“…The results of this paper will be of help to the users in identifying the best technique of terrain visualisation suitable for GIS data.…”
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Visualisation System of COVID-19 Data in Malaysia
Published 2021“…This study aims to provide a system, using COVID-19 data as a sample to visualise and analyse cases, deaths, discharged ICU cases updates in Malaysia as a whole state wise of COVID-19 daily statistics. …”
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A COMPARISON STUDY OF DATA CLUSTERING AND VISUALISATION TECHNIQUES WITH VARIOUS DATA TYPES
Published 2020“…Clustering is used to identify the intrinsic grouping of a set of unlabelled data. It can be applied in data mining exploration and statistical data analysis. …”
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A hybrid model using genetic algorithm and neural network for predicting dengue outbreak
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…This algorithm maintains the local optimal radius of micro-clusters rather than a global and constant radius. …”
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Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar
Published 2016“…Determining the suitable algorithm which can bring the optimized group clusters could be an issue. …”
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Improved Malware detection model with Apriori Association rule and particle swarm optimization
Published 2019“…Particle swarm optimization (PSO) is used to optimize the random generation of candidate detectors and parameters associated with apriori algorithm (AA) for features selection. …”
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