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A Data Mining Approach to Construct Graduates Employability Model in Malaysia
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A data mining approach to construct graduates employability model in Malaysia
Published 2011“…The performance of Bayes algorithms are also compared against a number of tree-based algorithms. …”
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Ant system-based feature set partitioning algorithm for classifier ensemble construction
Published 2016“…In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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Comparative assessment of rule-based and Bayes' theorem as inference engines in diagnosing symptoms for Islamic medication expert system
Published 2014“…An expert system for diagnosing sickness and suggesting treatment based on Islamic Medication (IM) was constructed using Rule Based (RB) and Bayes' theorem (BT) algorithms independently as its inference engine. …”
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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition
Published 2007“…In the initial stage, the dynamic Bayesian networks models are constructed based on a set of lexical cues selected tentatively from the dialogue corpus. …”
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Thesis -
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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms
Published 2023“…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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Final Year Project Report / IMRAD -
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Urban landcover features identification utilizing multiband combinations and multi-level image segmentation for objectbased classification / Nurhanisah Hashim
Published 2018“…Three supervised object based classifier namely Support Vector Machine (SVM), BAYES and K-Nearest Neighbour (KNN) were tested in order to identify which classifier gives the best classification result of the urban area of the study. …”
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Final Year Project -
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Final Year Project -
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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.]
Published 2024“…This study has investigated five commonly used machine learning algorithm to be constructed as potential models for predicting stroke dataset. …”
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An improved multiple classifier combination scheme for pattern classification
Published 2015“…Experiments were performed using four base classifiers, which are Nearest Mean Classifier (NMC), Naive Bayes Classifier (NBC), k-Nearest Neighbour (k-NN) and Linear Discriminant Analysis (LDA) on benchmark datasets, to test the credibility of the proposed multiple classifier combination scheme. …”
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Thesis -
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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…Applying Data Mining techniques in an educational environment are known as Educational Data Mining that aims to discover hidden knowledge and patterns about students’ behaviour. …”
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E4ML: Educational Tool for Machine Learning
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A study of feature selection algorithms for predicting students academic performance
Published 2018“…In EDM, Feature Selection (FS) plays a vital role in improving the quality of prediction models for educational datasets. FS algorithms eliminate unrelated data from the educational repositories and hence increase the performance of classifier accuracy used in different EDM practices to support decision making for educational settings. …”
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A study of feature selection algorithms for predicting students academic performance
Published 2018“…In EDM, Feature Selection (FS) plays a vital role in improving the quality of prediction models for educational datasets. FS algorithms eliminate unrelated data from the educational repositories and hence increase the performance of classifier accuracy used in different EDM practices to support decision making for educational settings. …”
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DESIGN AND DEVELOPMENT OF ANDROID-BASED LEARNING MEDIA FOR LEARNING ALGORITHM AND DATA STRUCTURE
Published 2021“…This study aims to design learning media algorithms and data structures based on Android. The research method uses a waterfall-type system development life cycle (SDLC). …”
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Proceeding -
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Predicting the popularity of tweets using the theory of point processes.
Published 2019“…The knowledge is combined using a novel empirical Bayes type approach, where the prior distribution for the model parameter is constructed based on the external knowledge, and the likelihood is calculated based on the internal knowledge. …”
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UMK Etheses -
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Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making
Published 2024“…The study’s primary objectives were to identify the determinants that impacted urban upper-secondary students' enrolment in Additional Mathematics within the Kuantan District, Pahang, Malaysia, and to develop a novel modified stacked ensemble statistical learning-based algorithm based on potential determinants, following the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology. …”
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