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Data Classification and Its Application in Credit Card Approval
Published 2004“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation
Published 2023“…Grid search cross validation (CV) is applied for hyperparameter tuning of the algorithms. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…Finally, the proposed algorithms were also validated on another dataset of a university campus in a different region. …”
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Thesis -
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Knowledge discovery in distance relay event report: a comparative data-mining strategy of rough set theory with decision tree
Published 2010“…These rules would then be compared with and validated by benchmarking decision-tree-based data-mining analysis.…”
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Application of sampling-based motion planning algorithms in autonomous vehicle navigation
Published 2016“…The performance of the proposed method is tested through simulation in different scenarios and also by comparing the performances of RRT and RRT* algorithms. The proposed method provides near-optimal solutions with smaller trees and in lower running time.…”
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Book Section -
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Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure
Published 2011“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Conference or Workshop Item -
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Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob
Published 2022“…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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Thesis -
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Neutralisation state driven single-agent search strategy for solving constraint satisfaction problem / Saajid Akram Ahmed Abuluaih
Published 2019“…Since Constraint Satisfaction Problem (CSP) is an NP-complete problem, brute-force search algorithms such as Backtracking algorithm (BT) are required as the guarantee to find a solution, when there is one. …”
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Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia
Published 2025“…The effectiveness of ITPS was evaluated using five machine learning algorithms: J48, Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbors. …”
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Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…In addition, a graph algorithm based on greedy methods is employed to compute a new set of optimal weighted electronic properties of the fullerenes via computing their Minimum Weight Spanning Trees (MWSTs). …”
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Thesis -
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Artificial intelligence in diagnosing tuberculosis: a review
Published 2019“…In the past fifty years, due to the advanced and sophisticated technologies, in medical as well as computer science fields, have paved a way to utilize the essence of both the areas. In Artificial Intelligence (AI) various Machine Learning (ML) algorithms have furthered the interests in Computer-aided Detection (CADe) and Diagnosis (CADx) methods. …”
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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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Intelligent Optimization Systems for MaintenanceScheduling of Power Plant Generators
Published 2024“…The intelligent optimization models are developed using MATLAB and the developed intelligent algorithms are tested on a case study in a coal power plant located at minjung, Perak, Malaysia. …”
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