Search Results - (( java implementation bayes algorithm ) OR ( program solution tree algorithm ))
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…In this system, the layout was designed under two categories which are the standard bay size and the small bay size to increase the parking bays. …”
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Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…The algorithmic solution with some strategies mainly focuses on efficiency. …”
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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 support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor
Published 2024“…Subsequently, predictive models employing k-nearest neighbour and decision tree algorithms are constructed and evaluated based on accuracy, precision, and recall metrics. …”
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Optimizing the carbon absorption of palm oil plantation in Negeri Sembilan / Hannis Syazani Zulkefle, Nur Nazirah Mohd Nazri and Nur Shahirah Mohd Shafie
Published 2019“…Data was collected from Malaysian Palm Oil Board (MPOB). The Simplex Algorithm in Linear Programming Method using QM for Windows is applied to find the solution. …”
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Implementation of Health Monitoring System for Patients using Machine Learning Algorithms
Published 2024“…We employed the Decision Tree Algorithm to train and assess a model that produced a perfection of 66.66%.…”
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Towards a better feature subset selection approach
Published 2010“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Conference or Workshop Item -
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Classification models for higher learning scholarship award decisions
Published 2018“…In addition, the knowledge analysis of the decision tree model was also made and found that some new information derived from the acquisition of this research information may help the stakeholders in making new policies and scholarship programs in the future.…”
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