Search Results - (( parameter optimization mining algorithm ) OR ( using vectorization based 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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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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Thesis -
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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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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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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Basically, the proposed of FUHS16, UHDS16 and UHDS8 algorithm produces the best motion vector estimation finding based on the block-based matching criteria. …”
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Book Chapter -
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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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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA)
Published 2021“…Support Vector Machine (SVM) technique is used with the Whale Optimization Algorithm (WOA) which is inspired by the swarm optimization algorithms. …”
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Proceeding Paper -
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Enhanced ontology-based text classification algorithm for structurally organized documents
Published 2015“…This research combines the ontology and text representation for classification by developing five algorithms. The first and second algorithms namely Concept Feature Vector (CFV) and Structure Feature Vector (SFV), create feature vector to represent the document. …”
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A hybrid model using genetic algorithm and neural network for predicting dengue outbreak
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Conference or Workshop Item -
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Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
Published 2021“…This work aims to model the combined cycle power plant (CCPP) using different algorithms. The algorithms used are Ridge, Linear regressor (LR), and support vector regressor (SVR). …”
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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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Using the bees algorithm to optimise a support vector machine for wood defect classification
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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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An ensemble data summarization approach based on feature transformation to learning relational data
Published 2015“…The Information Gain borrowed from Information Retrieval theory and Term-term Correlation algorithm are used to determine the relevancy of these features to be selected or merged in order to form a new generation of TF-IDF vector space. …”
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