Search Results - (( developing knowledge svm algorithm ) OR ( java implication based algorithm ))
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A Knowledge Management System for Assessing Lecturer Competence in Indonesian Higher Educational Institutions
Published 2025“…Lecturer competency measurement is carried out by first checking employee status using the SVM algorithm with an accuracy value of 72.28%, then using a hybrid SVM and PSO algorithm with an accuracy value of 100%. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
Published 2014“…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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Research Reports -
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Multilingual Sentiment Analysis From Students Feedback: Optimal Techniques And Resources For Bengali Lingual Data
Published 2024thesis::doctoral thesis -
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Classification models for higher learning scholarship award decisions
Published 2018“…A dataset of successful and unsuccessful applicants was taken and processed as training data and testing data used in the modelling process. 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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Development of colorization of grayscale images using CNN-SVM
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Book Chapter -
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Support vector machine in precision agriculture: a review
Published 2021“…To our knowledge, this review highlights and summarizes recently renewed efforts of improving SVM performance in PA through its integration with DL, which is believed to be an upcoming trend for ML model development in modern PA.…”
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Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve hig...
Published 2022“…One of the most commonly used algorithms is Support Vector Machine (SVM). However, classical SVM can neither use prior knowledge to process accurate classifications nor solve problems characterized by ambiguity. …”
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Sentiment analysis of customer review for Tina Arena Beauty
Published 2025“…Three machine learning algorithms Naive Bayes, Random Forest, and Support Vector Machine (SVM) were evaluated, and SVM achieved the highest accuracy and was selected as the final classifier. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The second stage is detecting jammers by integrating both lower layers by developing Integrated Combined Layer Algorithm (ICLA). …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Physiological signals as predictors of mental workload: Evaluating single classifier and ensemble learning models
Published 2023“…The ndings indicate that most HRV features differ signicantly during periods of mental workload compared to rest phases. The SVM classier with knowledge domain selection and leave-one-out cross-validation technique is the best model (68.385). …”
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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Monograph -
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd...
Published 2024“…Discriminant function analysis (DFA), binary logistic regression (BLR), and several machine learning (ML) algorithms (random forest (RF), support vector machines (SVM), and linear discriminant analysis (LDA)) were used to statistically analyse the data. …”
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