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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…Ant-tree-miner (ATM) has an advantage over the conventional decision tree algorithm in terms of feature selection. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Comparative study of clustering-based outliers detection methods in circularcircular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. …”
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Parsing algorithms for grammars with regulated rewriting
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Proceeding Paper -
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Adaptive resource allocation algorithms with QoS support based on network conditions using fuzzy logic system for IEEE 802.11n networks / Bakeel Hussein Naji Maqhat
Published 2016“…The first contribution is the AMS scheduling algorithm. The aim is to satisfy QoS requirements for time sensitive applications by exploiting the A-MSDU attributes and adopting the idea of enabling selective retransmission in our scheduling algorithm to obtain aggregation with small size to support time-sensitive applications and enable prioritization according to the QoS requirements of the traffic classes. …”
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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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A study of watermarking methods in medical application
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Loop-based RSA Key Generation Algorithm using String Identity
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. …”
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Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
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Proceeding Paper -
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Cryptanalytic attacks on Rivest, Shamir, and Adleman (RSA) cryptosystem: issues and challenges
Published 2014“…Generally RSA algorithm gain a security support because of it’s frequently use in most applications where security of digital data is mostly a concern. …”
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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow
Published 2023“…Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…From the enriched GO tree, the BTreeBicluster algorithm is applied during the clustering process. …”
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Monograph -
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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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