Search Results - evolution ((classification techniques) OR (((mining techniques) OR (learning techniques))))

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  1. 1

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

    Published 2004
    “…Many statistical and data mining techniques have been used to predict time series stock market. …”
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    Article
  2. 2

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

    Published 2015
    “…The significance of classifying cancer patients has led numerous research parties, from the bioinformatics and the biomedical domains, to rout out the enforcement of data mining methods. The fundamental target of data mining and machine learning is to achieve efficacious cancer classification mechanisms which provide considerable and trustworthy classification accuracy. …”
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    Proceeding Paper
  3. 3

    A review of homogenous ensemble methods on the classification of breast cancer data by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2024
    “…As evolution happens, ensemble methods are being proposed to achieve better performance in classification. …”
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    Article
  4. 4

    A review of homogenous ensemble methods on the classification of breast cancer data by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2024
    “…As evolution happens, ensemble methods are being proposed to achieve better performance in classification. …”
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    Article
  5. 5

    Data mining in computer auditing / Hiromi Wong, Siew Lan and Valery Fred Lee by Hiromi , Wong, Siew , Lan, Valery, Fred Lee

    Published 2004
    “…The report will cover the literature review that started with an introduction to computer auditing, introduction to data mining, data mining techniques (classification, neural network and sequential analysis), and the existing data mining software. …”
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    Thesis
  6. 6

    Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

    Published 2025
    “…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
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    Article
  7. 7

    Global Trends of Educational Data Mining in Online Learning by Chen, Chwen Jen, Teh, Chee Siong, Dexter Sigan, John

    Published 2023
    “…Educational data mining (EDM) in online learning involves data mining techniques to analyze data from online environments to gain insights into student behavior, performance, and engagement. …”
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    Article
  8. 8

    Stacking with recursive feature elimination-isolation forest for classification of diabetes mellitus by Nur Farahaina, Idris, Mohd Arfian, Ismail, Mohd Izham, Mohd Jaya, Ashraf Osman, Ibrahim, Abulfaraj, Anas W., Binzagr, Faisal

    Published 2024
    “…Among the advanced data mining techniques in artificial intelligence, stacking is among the most prominent methods applied in the diabetes domain. …”
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  9. 9

    Stacking with recursive feature elimination-isolation forest for classification of diabetes mellitus by Nur Farahaina, Idris, Mohd Arfian, Ismail, Mohd Izham, Mohd Jaya, Ashraf Osman, Ibrahim, Abulfaraj, Anas W., Binzagr, Faisal

    Published 2024
    “…Among the advanced data mining techniques in artificial intelligence, stacking is among the most prominent methods applied in the diabetes domain. …”
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    Article
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    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…The performance of proposed method is compared with several feature selection techniques in order to prove their superiority using ten datasets obtained from UCI machine learning repository.…”
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    Article
  12. 12

    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…Results show that the best feature selection is term frequency and trimming of the feature with a frequency greater than 95%. The best news classification approach is based on Deep Learning techniques that provide the most accurate classification. …”
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    Book Section
  13. 13

    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
  14. 14

    Global trends of educational data mining in online learning by Nie Hui Ling, Chwen Jen Chen, Chee Siong Teh, Dexter Sigan John, Looi Chin Ch’ng, Yoon Fah Lay

    Published 2023
    “…Educational data mining (EDM) in online learning involves data mining techniques to analyze data from online environments to gain insights into student behavior, performance, and engagement. …”
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    Article
  15. 15

    A New Hybrid K-Means Evolving Spiking Neural Network Model Based on Differential Evolution by Abdulrazak Yahya, Saleh, Haza Nuzly, Abdull Hamed, Siti Mariyam, Shamsuddin, Ashraf, Osman Ibrahim

    Published 2018
    “…Clustering is one of the essential unsupervised learning techniques in Data Mining. In this paper, a new hybrid (K-DESNN) approach to combine differential evolution and K-means evolving spiking neural network model (K-means ESNN) for clustering problems has been proposed. …”
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    Book Chapter
  16. 16

    Accelerator-based human activity recognition using voting technique with NBTree and MLP classifiers by Azmi M.S.M., Sulaiman M.N.

    Published 2023
    “…In this study, an accelerator-based activity recognition model using voting technique was proposed. Two machine learning classifiers, Naive Bayes Tree (NBTree) and Multilayer Perceptron (MLP), were used as ensemble classifiers in the voting technique. …”
    Article
  17. 17

    Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

    Published 2020
    “…However, in this project, deep learning techniques are used in developing a model for diseases and pest detection in plants, and then train and test the model before eventually integrating the model into a mobile application. …”
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    Final Year Project / Dissertation / Thesis
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    A joint learning classification for intent detection and slot filling from classical to deep learning: a review by Muhammad Yusuf, Idris, Naomie, Salim, Anazida, Zainal, Sinarwati, Mohamad Suhaili

    Published 2025
    “…It discusses the limitations of classical models, which led to the rise of deep learning techniques, and introduces a new taxonomy for joint learning classifying joint learning architectures. …”
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    Article
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    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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    Conference or Workshop Item
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