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3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm
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Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…Four conventional classification algorithms: naïve bayes (NB), support vector machines (SVM), nearest neighbor (k-NN), and decision trees (J48) classifiers are implemented in identifying and categorizing tweet data of three political figures in Malaysia: Dato Seri Anwar, Dato Hadi Awang, and Lim Guang Eng, as either positive, negative, or neutral perceptions. …”
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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali
Published 2025“…This study explores the application of sentiment analysis using the Naive Bayes algorithm to understand public perceptions of marital issues, particularly factors contributing to the rising divorce rate. …”
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A literature review on text classification and sentiment analysis approaches
Published 2021“…Sentiment analysis is an important branch task of text classification and the related system usually is applied to in perception of user emotion and public opinion monitoring. …”
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Prediction of college student academic performance using data mining techniques.
Published 2013“…This study attempts to predict the success rate of students’ academic performance by analyzing their examination results to secure a place at college level for the subsequent semester. The classification algorithms used are the Decision Tree, Naïve Bayesian, and Multilayer Perception with the highest classification accuracy by the Naive Bayes algorithm with accuracy of 95.3%. …”
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Design of a pattern classification system using extreme learning machine
Published 2024text::Final Year Project -
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Design of a pattern classification system using extreme learning machine
Published 2023text::Final Year Project -
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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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Advancing literary analysis with Python: a comprehensive study of simile detection and classification in the translation of Al-Abrat
Published 2025“…The research employs Abdul-Raof’s classification framework, combining traditional Arabic rhetorical theory with computational methods, including Python-based algorithms, to detect and categorize similes. …”
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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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A rule-based image segmentation method and neural network model for classifying fruit in natural environment / Hamirul'aini Hambali
Published 2015“…This robust method is able to segment images for all categories of objects at a commendable percent accuracy rate. For object classification, some methods have the ability to identify objects as good as human experts who normally classify objects based on visual perception. …”
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Multilanguage speech-based gender classification using time-frequency features and SVM classifier
Published 2021“…The classification is done based on features derived from the frequency and time domain processing using the Support Vector Machines (SVM) algorithm. …”
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Integration of MFCCS and CNN for multi-class stress speech classification on unscripted dataset
Published 2024“…Leveraging deep learning technology, specifically Convolutional Neural Network (CNN), our research optimally combines speech features and CNN algorithms for stress classification. Despite the scarcity of publications on unscripted datasets and multi-class stress classifications, our study advocates their adoption, aiming to enhance performance metrics and contribute to research expansion. …”
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