Search Results - (( java implementation tree algorithm ) OR ( programme e learning algorithm ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Predicting usage for a marketable e-learning portal
Published 2014“…To date, existing e-learning portals focuses on providing various learning materials via online.Such an approach may provide huge benefit to the learners; nevertheless, less value can be obtained by the developers or owners.The knowledge transfer programme provides an insight on how existing e-learning portal can be upgraded.The academia has introduced the industry to a computational modelling that is built upon the behaviour of nature community (i.e bees)The utilization of Artificial Bee Colony algorithm in predicting learners' usage of an e-learning portal provides an indicator to the developers on the portals effectiveness.Such information is then useful in producing a marketable and valuable e-learning portal…”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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CT-eKit: computational thinking interactive learning / Ong Sing Ling, Jill Ling and Fetylyana Nor Pazilah
Published 2023“…A mixed method was employed to investigate the students' learning experience with CT-eKit. This study involved 120 students from the Foundation in Science programme of the University of Technology Sarawak (UTS). …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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Using web questionnaire for web-based course evaluation: advantages and disadvantages
Published 2017“…Creating and conducting a Web survey is a task requiring familiarity with Web programmes and database. This article examines some advantages and disadvantages of conducting Web survey research especially for Web-based course evaluation at Iranian university E-learning centers. …”
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Ensemble learning for multidimensional poverty classification
Published 2020“…The goal of this study was to determine whether ensemble learning method (random forest) can classify poverty and hence produce multidimensional poverty indicator compared to based learner method using eKasih dataset. …”
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Beyond Grades - Predicting Programme Learning Outcomes with Multi-Output Regression in Malaysian Higher Education
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The identification of high potential archers based on relative psychological coping skills variables: a support vector machine approach
Published 2018“…Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. …”
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The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach
Published 2018“…Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. …”
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The employment of support vector machine to classify high and low performance archers based on bio-physiological variables
Published 2018“…The present study employs a machine learning algorithm namely support vector machine (SVM) to classify high and low potential archers from a collection of biophysiological variables trained on different SVMs. 50 youth archers with the average age and standard deviation of (17.0 +/-.056) gathered from various archery programmes completed a one end shooting score test. …”
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The employment of Support Vector Machine to classify high and low performance archers based on bio-physiological variables
Published 2018“…The present study employs a machine learning algorithm namely support vector machine (SVM) to classify high and low potential archers from a collection of bio-physiological variables trained on different SVMs. 50 youth archers with the average age and standard deviation of (17.0 ±.056) gathered from various archery programmes completed a one end shooting score test. …”
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