Search Results - (( model validation step algorithm ) OR ( miner classification learning algorithm ))
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1
A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…The successful work on hybridization of ACO and SA algorithms has led to the improved learning ability of ACO for classification. …”
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Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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Hybrid ant colony optimization and genetic algorithm for rule induction
Published 2020“…In this study, a hybrid rule-based classifier namely, ant colony optimization/genetic algorithm ACO/GA is introduced to improve the classification accuracy of Ant-Miner classifier by using GA. …”
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An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka
Published 2024“…By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. …”
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method
Published 2023“…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani
Published 2021“…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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Implementation of machine learning algorithm in preventing network congestion
Published 2023text::Final Year Project -
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Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique
Published 2021“…Conclusion. Machine learning algorithms can produce a highly accurate postsurgery classification model of BCVA changes using pterygium characteristics.…”
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Development of predictive modeling and deep learning classification of taxi trip tolls
Published 2022“…Several studies discussed the predictive modeling of deep learning in different applications such as classifying tissue features from microstructural data, Crude Oil Prices, mechanical constitutive behavior of materials, microbiome data, and mineral prospectively. …”
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Performance of Semi Active Lateral Control (SALC) algorithm for semi active suspension system in multibody co-simulation method / M. M. Abdul Majid ...[et al.]
Published 2018“…New controller algorithm (SALC) was than developed in Matlab/Simulink and integrate with correlated vehicle plant model for handling performance validation against passive suspension and Skyhook. …”
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…Meanwhile, practitioners who are usually non-experts and lack of statistical knowledge will face difficulties during the modelling process. Hence, algorithm with a step by step guidance is beneficial in model building, testing and selection. …”
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DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS
Published 2023“…Several studies discussed the predictive modeling of deep learning in different applications such as classifying tissue features from microstructural data, Crude Oil Prices, mechanical constitutive behavior of materials, microbiome data, and mineral prospectively. …”
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A Model for Evaluation of Cryptography Algorithm on UUM Portal
Published 2004“…The development of the simulation model consists of seven steps. The steps are problem definition, construct the simulation model, test and validate the model, design the simulation experiments, conduct the simulation experiments, evaluate the result and implement the result. …”
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17
Structural Equation Modeling Algorithm and Its Application in Business Analytics
Published 2017“…This review article algorithmically discussesthe SEM methodology. SEM strategies, SEM steps and SEM stages are introduced in this article; validity tests are presented os well. …”
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Book Chapter -
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Design and analysis of construction and recombination module using Idury Waterman Algorithm for fragment assembly application / Hafifi Mohd Rafi
Published 2012“…The result of the proposed algorithm, verifies the validity of proposed algorithm.…”
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Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model
Published 2018“…The seven sensitive kinetic parameters were used in both the algorithms to minimize the model response errors. The validation results proved the effectiveness of both the proposed methods, which identified the kinetics and minimized the model response errors perfectly.…”
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Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…A superior performance is achieved by the proposed algorithms in system modeling where the DQLMS was able to track the correct weights values of the different modeled systems 430 sample faster than the QLMS and ZA-QLMS algorithms while the WL-DQLMS was faster than the WLQLMS algorithm by 950 samples. …”
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Thesis
