Search Results - (( developing systematic mining algorithm ) OR ( java application stemming algorithm ))

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    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Moreover, this study introduces a mining algorithm called PC-miner to mine the mining model frequently with various values of minsup. …”
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    Thesis
  3. 3

    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

    Published 2024
    “…The developed logic mining will be used to analyze the Alzheimer's Disease Neuroimaging Initiative dataset.…”
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  4. 4

    Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

    Published 2014
    “…Works on sustaining the interestingness of rules generated by data mining algorithms are actively and constantly being examined and developed. …”
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  5. 5

    Synergizing intelligence and knowledge discovery: Hybrid black hole algorithm for optimizing discrete Hopfield neural network with negative based systematic satisfiability by Rusdi, Nur ‘Afifah, Zamri, Nur Ezlin, Kasihmuddin, Mohd Shareduwan Mohd, Romli, Nurul Atiqah, Manoharam, Gaeithry, Abdeen, Suad, Mansor, Mohd. Asyraf

    Published 2024
    “…Based on the findings, the development of the new systematic SAT and the implementation of the Hybrid Black Hole algorithm to optimize the retrieval capabilities of DHNN to achieve multi-objective functions result in updated final neuron states with high diversity, high attainment of global minima solutions, and produces states with a low similarity index. …”
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    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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  9. 9

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
  10. 10

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
  11. 11

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
  12. 12

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

    Published 2023
    “…Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
  13. 13

    Portfolio optimization with percentage error-based fuzzy random data for industrial production by Othman, Mohammad Haris Haikal, Arbaiy, Nureize, Che Lah, Muhammad Shukri, Pei, Chun Lin

    Published 2024
    “…The proposed framework not only acknowledges the importance of data preprocessing but also offers a systematic approach to processing fuzzy random data, thus providing a robust foundation for portfolio selection algorithms. …”
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  14. 14

    Portfolio optimization with percentage error-based fuzzy random data for industrial production by Othman, Mohammad Haris Haikal, Arbaiy, Nureize, Che Lah, Muhammad Shukri, Lin, Pei-Chun

    Published 2024
    “…The proposed framework not only acknowledges the importance of data preprocessing but also offers a systematic approach to processing fuzzy random data, thus providing a robust foundation for portfolio selection algorithms. …”
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    Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

    Published 2018
    “…A dataset of successful and unsuccessful applicants was taken and processed as training data and testing data used in the modelling process. Five algorithms were employed to develop a classification model in determining the award of the scholarship, namely J48, SVM, NB, ANN and RT algorithms. …”
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  17. 17

    Application of data mining techniques for economic evaluation of air pollution impact and control by Lukman, Iing

    Published 2007
    “…For that purpose, we use data mining techniques. Data mining techniques applied in this thesis were: 1) Group method of data handling (GMDH), originally from engineering, introducing principles of evolution - inheritance, mutation and selection - for generating a network structure systematically to develop the automatic model, synthesis, and its validation; 2) The weighted least square (WLS) and step wise regression were also applied for some cases; 3) The classification-based association rules were applied. …”
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    Thesis
  18. 18

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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    Understanding the occurrence of metastatic breast cancer through clinical, phenotype and genotype data, and the employment of machine learning / Nadia Jalaludin by Jalaludin, Nadia

    Published 2023
    “…Therefore, the objective of this study is to: a) mine and integrate clinical, phenotype and genotype data that contributes to the occurrence of MBC, b) build a prediction model that can predict possibility of occurrence to metastatic state of breast cancer based on factors previously determined in (a), and c) to validate findings from (a) and (b) through systematic review of randomised controlled trials of MBC. …”
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    Thesis
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