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  1. 1
    Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems: A Medical Case Study

    Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems: A Medical Case Study by Got, Adel, Zouache, Djaafar, Moussaoui, Abdelouahab, Laith, Abualigah *, Alsayat, Ahmed

    Published 2024
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  2. 2
    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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    Thesis
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  3. 3
    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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  4. 4
    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol

    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

    Published 2023
    “…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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  5. 5
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    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. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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    Final Year Project
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  6. 6
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    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. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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    Final Year Project
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  7. 7
    Salivary based SERS analysia in recognition of NS1 for PCA-SVM classification of dengue fever / Afaf Rozan Mohd Radzol

    Salivary based SERS analysia in recognition of NS1 for PCA-SVM classification of dengue fever / Afaf Rozan Mohd Radzol by Mohd Radzol, Afaf Rozan

    Published 2018
    “…Finally, the extracted principal components are classified into dengue positive and negative using SVM algorithm. NS1 ELISA and NS1 Rapid serum tests result are used as benchmark against sensitivity, specificity and accuracy performance of the SVM algorithms in which three types of kernels i.e; Linear, RBF and MLP are optimized and compared. …”
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  8. 8
    Salivary based SERS analysis in recognition of NS1 for PCA-SVM classification of dengue fever / Afaf Rozan Mohd Radzol

    Salivary based SERS analysis in recognition of NS1 for PCA-SVM classification of dengue fever / Afaf Rozan Mohd Radzol by Mohd Radzol, Afaf Rozan

    Published 2018
    “…Finally, the extracted principal components are classified into dengue positive and negative using SVM algorithm. NS1 ELISA and NS1 Rapid serum tests result are used as benchmark against sensitivity, specificity and accuracy performance of the SVM algorithms in which three types of kernels i.e; Linear, RBF and MLP are optimized and compared. …”
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  9. 9
    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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  10. 10
    A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation

    A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

    Published 2023
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  11. 11
    Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms

    Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms by Masrom, S., Rahman, R.A., Mohamad, M., Rahman, A.S.A., Baharun, N.

    Published 2022
    “…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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  12. 12
    Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms

    Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms by Masrom, S., Rahman, R.A., Mohamad, M., Rahman, A.S.A., Baharun, N.

    Published 2022
    “…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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  13. 13
    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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    Conference or Workshop Item
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  14. 14
    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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    Final Year Project / Dissertation / Thesis
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  15. 15
    Salivary based sers analysis in recognition of ns1 for pcasvm classification of dengue fever / Afaf Rozan Mohd Radzol

    Salivary based sers analysis in recognition of ns1 for pcasvm classification of dengue fever / Afaf Rozan Mohd Radzol by Mohd Radzol, Afaf Rozan

    Published 2018
    “…Finally, the extracted principal components are classified into dengue positive and negative using SVM algorithm. NS1 ELISA and NS1 Rapid serum tests result are used as benchmark against sensitivity, specificity and accuracy performance of the SVM algorithms in which three types of kernels i.e; Linear, RBF and MLP are optimized and compared. …”
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    Book Section
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  16. 16
    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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    Citation Index Journal
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  17. 17
    Optimized techniques for landslide detection and characteristics using LiDAR data

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
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  18. 18
    Developing flood mapping procedure through optimized machine learning techniques. Case study: Prahova river basin, Romania

    Developing flood mapping procedure through optimized machine learning techniques. Case study: Prahova river basin, Romania by Diaconu D.C., Costache R., Towfiqul Islam A.R.M., Pandey M., Pal S.C., Mishra A.P., Pande C.B.

    Published 2025
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  19. 19
    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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  20. 20
    Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia

    Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia by Latif S.D., Ahmed A.N., Sathiamurthy E., Huang Y.F., El-Shafie A.

    Published 2023
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