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1
An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Differing from other complex and difficult classification models, rules-based classification algorithms produce models which are understandable for users. …”
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2
An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…This research is mainly about improving existing classification algorithms for a correct classification results and evaluating the accuracy of classification algorithms in correctly determining urban growth forms, The datasets are Landsat Thematic Mapper (TM) images of Klang Valley, one of the most rapid urban growth areas in Malaysia. …”
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3
Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…Each image went through the embedding process by the evaluated algorithms. This enhanced image data numbers then went through Logistic Regression as a classifier. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons
Published 2020“…This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
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6
Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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8
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…The evaluation showcases significant improvements, with the test ML model achieving a best accuracy score of 0.571, a 46% increase from the baseline, and a best F1 score of 0.727, a 30% increment from the baseline. …”
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9
Academic leadership bio-inspired classification model using negative selection algorithm
Published 2015“…Several experiments were carried out by using different set of training and testing data-sets to evaluate the accuracy of the proposed model.As a result, the accuracy of the proposed model is considered excellent for academic leadership classification.For future work, in order to enhance the proposed bio-inspired classification model, a comparative study should be conducted using other established artificial immune system classification algorithms i.e. clonal selection and artificial immune network.…”
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Dingle's Model-based EEG Peak Detection using a Rule-based Classifier
Published 2015“…Rule-based classifier with an estimation technique based on particle swarm optimization (PSO) is employed in the classification stage. …”
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Hybrid performance measures and mixed evaluation method for data classification problems
Published 2012“…From all evaluations, it clearly reveals that the OAERP2 measure is able to choose a better solution during the classification training. …”
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Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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Classification models for higher learning scholarship award decisions
Published 2018“…Five algorithms were employed to develop a classification model in determining the award of the scholarship, namely J48, SVM, NB, ANN and RT algorithms. …”
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Fusion of moment invariant method and deep learning algorithm for COVID-19 classification
Published 2021“…This paper proposes a fusion of a moment invariant (MI) method and a DL algorithm for feature extraction to address the instabilities in the existing COVID-19 classification models. …”
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Accuracy assessment of Digital Terrain Model (DTM) Constructed Cloth Simulation Filter (CSF) and Multi Curvature Classification (MCC) algorithm on UAV LiDAR dataset / Mohamad Khair...
Published 2023“…This study aims to evaluate the effectiveness of open-source software algorithms for ground classification in lidar point clouds and the subsequent generation of accurate DTMs. …”
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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The performance of algorithms was measured based on classification accuracy, error rate, and precision and recall. …”
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17
Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi
Published 2012“…In order to develop this model classification and prototype, 480 Twitter’s messages were used as training data and 120 Twitter’s messages for testing data to determine the accuracy of the classification model. …”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
Published 2024journal::journal article -
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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