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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The supervised machine learning algorithm, SVM and Decision Tree are used for the estimation of the mangrove age into young and mature. …”
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Thesis -
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Classification of basal stem rot disease in oil palm using dielectric spectroscopy
Published 2018“…For feature selection algorithms, SVM-FS model gave the best classification accuracies compared to GA and RF; ranged from 81.82% to 88.64% with SVM and kNN as the best classifiers. …”
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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Final Year Project -
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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Final Year Project -
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A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment
Published 2024Proceedings Paper -
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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A study on classification learning algorithms to predict crime status.
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Sentiment Analysis on Users' Satisfaction for Mobile Banking Apps in Malaysia
Published 2022“…The dataset was compared with five algorithms: Linear Regression, Naïve Bayes, Decision Tree, Random Forest, and Support Vector Machine (SVM). …”
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Enhanced faster region-based convolutional neural network for oil palm tree detection
Published 2021“…It can only extract low-middle level features from the image and lack of generalization ability. It’s applicable only for one application and will need reprogramming for other applications. …”
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A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems
Published 2023“…The developed ML model successfully estimated the sediment load with competitive results from ANN, Decision Tree, AdaBoost and SVM. The best result was produced by SVM (v-SVM version) where very low RMSE was generated for both training and testing dataset despite its more complicated hyperparameters setup. …”
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Named entity recognition using a new fuzzy support vector machine.
Published 2008“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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Performance of Sentinel-2A remote sensing system for urban area mapping in Malaysia via pixel-based and OBIA methods
Published 2021“…Pixel-based and object-based image analysis (OBIA) classification approaches combined with support vector machine (SVM) and decision tree (DT) algorithms were utilized in this assessment, and the accuracy generated was analysed. …”
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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. …”
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Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…However, other classifiers like Decision Tree and kNN had 100% accuracy too. This means that the proposed system achieved its goals. …”
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Proceeding Paper -
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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm
Published 2013“…Each bat in Bat Algorithm represents a candidate solution for the problem and each dimension in the search space of the Bat Algorithm represents a parameter of intrinsic parameters: skew, focal length, and magnification factor. …”
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Design of Predictive Model for TCM Tongue Diagnosis In Malaysia Using Machine Learning
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Final Year Project / Dissertation / Thesis -
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