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

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  1. 1

    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
  2. 2

    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
  3. 3

    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
  4. 4

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

    Published 2015
    “…The evolution of authoritative immunofingerprint mining technology is exerting a growing influence on comprehensive cancer diagnosis biology. …”
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    Proceeding Paper
  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

    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
  7. 7

    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
  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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    Article
  9. 9

    Overview and future opportunities of sentiment analysis approaches for big data by Mohd Sharef, Nurfadhlina, Mat Zin, Harnani, Nadali, Samaneh

    Published 2016
    “…The contribution of this paper is two-fold: (i) this study reviews the state of the art of SA approaches. including sentiment polarity detection, SA features (explicit and implicit), sentiment classification techniques and applications of SA and (ii) this study reviews the suitability of SA approaches for application in the big data frameworks, as well as highlights the gaps and suggests future works that should be explored. …”
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    Article
  10. 10

    Thermosonic micro-interconnections: Interfacial Cu-Al intermetallics compound growth studies based on stress modelling by Sharir, Shariza

    Published 2024
    “…The results of the stress modelling could be a useful failure analysis technique for implementing Cu wire in the industry. …”
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    Thesis
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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
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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    Article
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    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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    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
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    Analysis on target detection and classification in LTE based passive forward scattering radar by Raja Abdullah, Raja Syamsul Azmir, Abdul Aziz, Noor Hafizah, Abdul Rashid, Nur Emileen, Salah, Asem Ahmad, Hashim, Fazirulhisyam

    Published 2016
    “…By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. …”
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    Article
  20. 20

    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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