Search Results - (( _ classification method algorithm ) OR ( data implication learning algorithm ))
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…Thus, this paper proposed metaheuristic algorithms such as Particle Swarm Optimization, Ant Colony Algorithm and Harmony Search Algorithm based feature selection to identify the most significant features of skeleton remains. …”
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Systematic review for phonocardiography classification based on machine learning
Published 2023“…This systematic review aims to examine the existing literature on phonocardiography classification based on machine learning, focusing on algorithms, datasets, feature extraction methods, and classification models utilized. …”
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Systematic Review for Phonocardiography Classification Based on Machine Learning
Published 2023“…This systematic review aims to examine the existing literature on phonocardiography classification based on machine learning, focusing on algorithms, datasets, feature extraction methods, and classification models utilized. …”
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Consumer acceptance and perceptions of electric vehicles in Malaysia using sentiment analysis
Published 2025“…The machine learning algorithm, support vector machine (SVM), is then created to automatically identify and classify comments about EV acceptance and perception. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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Consumer acceptance and perceptions of electric vehicles in Malaysia using sentiment analysis
Published 2025“…The machine learning algorithm, support vector machine (SVM), is then created to automatically identify and classify comments about EV acceptance and perception. …”
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XAIRF-WFP: a novel XAI-based random forest classifier for advanced email spam detection
Published 2024“…Traditional machine learning algorithms such as Logistic Regression (LR), K-Nearest Neighbors (KNN), Decision Trees (DT), and Support Vector Machines (SVM) have been employed to mitigate this challenge. …”
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Analysis On QOS Parameters To Predict Http Response
Published 2017“…Therefore, the real live world web service label data uses to evaluate the focus parameters using classification machine learning algorithms to process the data. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. …”
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…This method carries the advantages of the two previous methods in order to improve the classification tasks. …”
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification
Published 2023“…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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Knowledge base processing method based on text classification algorithm
Published 2023“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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Overview of metaheuristic: classification of population and trajectory
Published 2010“…An algorithm that applies a metaheuristic method is used when there are no specific methods to find a solution. …”
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Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…This method carries the advantages of the two previous methods in order to improve the classification tasks. …”
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An extended oversampling method for imbalanced Quranic text classification based on a genetic algorithm
Published 2023“…This abnormal distribution makes it difficult to obtain a consistent and balanced dataset, which can weaken the overall classification performance. To address this issue, this paper proposes a new oversampling method that employs Genetic algorithm to generate an optimal and balanced dataset simultaneously. …”
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Aco-based feature selection algorithm for classification
Published 2022“…The proposed EGCACO algorithm can be utilised for FS in DNA microarray classification tasks that involve large dataset size in various application domains.…”
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