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Direct approach for mining association rules from structured XML data
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Thesis -
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Article -
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Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia
Published 2023“…A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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Conference or Workshop Item -
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Final Year Project / Dissertation / Thesis -
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The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers
Published 2024“…Conclusions: The Combat algorithm has reduced variability in radiomic features from different scanners. …”
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Article -
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Thesis -
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…While machine learning eliminates the requirement for manual feature selection when extracting significant information from predictor fields, considering multiple pivotal factors is essential. …”
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Mortality prediction in critically ill patients using machine learning score
Published 2020“…Various types of classification algorithms in machine learning were investigated using common clinical variables extracted from patient records obtained from four major ICUs in Malaysia to predict mortality and assign patient mortality risk scores. …”
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Proceeding Paper -
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Mortality prediction in critically ill patients using machine learning score
Published 2020“…Various types of classification algorithms in machine learning were investigated using common clinical variables extracted from patient records obtained from four major ICUs in Malaysia to predict mortality and assign patient mortality risk scores. …”
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Conference or Workshop Item -
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Classification Of Cervical Cancer Stage From Pap Smear Tests
Published 2019“…Feature extraction is then used to select the appropriate features that contribute most to the predicted variable from the image. …”
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Final Year Project -
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Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm
Published 2015“…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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Development of sorting system for oil palm in vitro shoots using machine vision approach
Published 2014“…Ultimately, the sorting algorithm performance came to be evaluated by support vector machine algorithm. …”
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Thesis -
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Development of a syncope classification algorithm from physiological signals acquired in tilt-table test
Published 2023“…Syncope also known as transient loss of consciousness which caused problem to human daily life. Since machine learning is much more advanced, classification of syncope can be done with machine learning. …”
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Final Year Project / Dissertation / Thesis -
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Antidepressant Treatment Response Prediction With Early Assessment of Functional Near-Infrared Spectroscopy and Micro-RNA
Published 2025“…The entire algorithm achieved a better performance through the radial basis function (RBF) support vector machine (SVM), with 82.70 accuracy, 78.44 sensitivity, 86.15 precision, and 91.02 specificity, respectively, when compared with conventional machine learning approaches that combine clinical, sociodemographic and genetic information as the predictor. …”
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Automated detection and evaluation of ischemic stroke on ct brain imaging using machine learning techniques
Published 2025“…This study investigates the application of machine learning algorithms for the detection of ischemic stroke using CT brain images. …”
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