Search Results - (( based visualisation learning algorithm ) OR ( evolution classification mining algorithm ))

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  1. 1

    Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

    Published 2015
    “…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
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    Proceeding Paper
  2. 2

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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    Thesis
  3. 3

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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    Article
  4. 4

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

    Published 2024
    “…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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    Thesis
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  7. 7

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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    Thesis
  8. 8

    Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

    Published 2021
    “…Hybrid combinations of feature selection, classification and visualisation using machine learning (ML) methods have the potential for enhanced understanding and 30-day mortality prediction of patients with cardiovascular disease using population-specific data. …”
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    Article
  9. 9

    Interactive framework for dynamic modelling and active vibration control of flexible structures by Mat Darus, Intan Zaurah, Mohd. Hashim, Siti Zaiton, Tokhi, M. O.

    Published 2008
    “…The design and implementation of the interactive learning system incorporating the simulation algorithms, modelling and control strategies, are developed using MATLAB. …”
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    Article
  10. 10

    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
  11. 11

    An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

    Published 2004
    “…The simulation algorithm and interactive environment thus developed and validated form suitable test and verification platforms for the development of AVC strategies for flexible structures as well as for learning and research purposes.…”
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    Thesis
  12. 12

    Optimizing E-commerce inventory management using a machine-learning approach by Ruonan, Zhao, Wong, Doris Hooi-Ten

    Published 2025
    “…In addition, clustering algorithms, including DBSCAN and K-means, were applied to segment customers based on purchasing behaviour, with DBSCAN achieving a Silhouette Score of 0.9708, suggesting well-separated clusters. …”
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    Article
  13. 13

    A survey of deep learning for lung disease detection on medical images: state-of-the-art, taxonomy, issues and future directions by Tao, Stefanus Hwa Kieu, Abdullah Bade, Mohd Hanafi Ahmad Hijazi, Hoshang Kolivand

    Published 2020
    “…The objectives of this paper are to present a taxonomy of the state-of-the-art deep learning based lung disease detection systems, visualise the trends of recent work on the domain and identify the remaining issues and potential future directions in this domain. …”
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    Article
  14. 14
  15. 15

    The summer heat of cryptojacking season : Detecting cryptojacking using heatmap and fuzzy by Ahmad Firdaus, Zainal Abidin, Aldharhani, Ghassan Saleh, Zahian, Ismail, Mohd Faizal, Ab Razak

    Published 2022
    “…For machine learning-based detection, it's important to find important features in a minimal amount of data. …”
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    Conference or Workshop Item
  16. 16

    Predictors on outcomes of cardiovascular disease of male patients in Malaysia using Bayesian network analysis by Nurliyana Juhan, Yong Zulina Zubairi, Ahmad Syadi Mahmood Zuhdi, Zarina Mohd Khalid

    Published 2023
    “…A bootstrap resampling approach was integrated into the structural learning algorithm to estimate probabilistic relations between the studied features that have the strongest influence and support. …”
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    Article
  17. 17

    Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb by Riyaz Ahamed , Ariyaluran Habeeb

    Published 2019
    “…Based on the outcome of the analysis, this research proposed a novel framework namely real-time anomaly detection based on big data technologies (RTADBDT), along with supporting implementation algorithms. …”
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    Thesis
  18. 18

    Forecasting utility management in UiTMCTKKT using predictive analytics / Nur Sufiah Muhammad Taufik by Muhammad Taufik, Nur Sufiah

    Published 2025
    “…Future iterations could also improve the system using real-time monitoring and machine-learning based predictive algorithms.…”
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    Thesis