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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    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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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    Machine learning classifications of multiple organ failures in a malaysian intensive care unit

    Machine learning classifications of multiple organ failures in a malaysian intensive care unit by Norliyana, Nor Hisham Shah, Normy Norfiza, Abdul Razak, Athirah, Abdul Razak, Asma’, Abu-Samah, Fatanah, M. Suhaimi, Ummu Kulthum, Jamaludin

    Published 2024
    “…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”
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  7. 7
    Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit

    Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

    Published 2025
    “…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”
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  8. 8
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  9. 9
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    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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  10. 10
    Performance analysis of machine learning algorithms for missing value imputation

    Performance analysis of machine learning algorithms for missing value imputation by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani, Emran, Nurul Akmar

    Published 2018
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  11. 11
    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm

    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm by Mohd Sharif, Sharifah, Mohd Kusin, Faradiella, Asha’ari, Zulfa Hanan, Aris, Ahmad Zaharin

    Published 2015
    “…This study aimed to determine the spatiotemporal pattern of the water quality data and identifying the sources of pollution in the Klang River Basin. 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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  12. 12
    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida

    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida by Nanyonga , Aziida

    Published 2019
    “…From a group of 1480 patients drawn from the Acute Coronary Syndrome Malaysian registry, 302 people satisfied the inclusion criteria, and 54 variables were duly considered. Combinations of feature selection and classification algorithms were used for mortality prediction post ACS. …”
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  13. 13
    Performance analysis of machine learning algorithms for missing value imputation

    Performance analysis of machine learning algorithms for missing value imputation by Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Emran, Nurul Akmar

    Published 2018
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  14. 14
    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management

    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…By employing these methods, organizations can effectively allocate resources and exercise control over costs. …”
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  15. 15
    Mortality prediction in critically ill patients using machine learning score

    Mortality prediction in critically ill patients using machine learning score by Dzaharudin, Fatimah, Md Ralib, Azrina, Jamaludin, Ummu Kulthum, Mat Nor, Mohd Basri, Tumian, Afidalina, Har, Lim Chiew, Ceng, T C

    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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  16. 16
    Mortality prediction in critically ill patients using machine learning score

    Mortality prediction in critically ill patients using machine learning score by Fatimah, Dzaharudin, Azrina, Md Ralib, Ummu Kulthum, Jamaludin, Mohd Basri, Mat Nor, Afidalina, Tumian, Har, Lim Chiew, Ceng, T. C.

    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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  17. 17
    Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0

    Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0 by Chong, Agnes Wen Lin

    Published 2023
    “…Thus, the secondary objective is to learn about the model including innovation, enterprise, and Ecological. …”
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  18. 18
    Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale

    Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale by Ameenuddin Irfan, S., Fadhli, M.Z., Padmanabhan, E.

    Published 2021
    “…The developed model has successful in prediction the contact angle for different input variables of the machine learning model with high r squared values. …”
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  19. 19
    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection

    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

    Published 2018
    “…Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. …”
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  20. 20
    Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers

    Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers by Siaw Hui, Teo

    Published 2025
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