Search Results - (( evolution classification modeling algorithm ) OR ( pattern extraction using algorithm ))

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  1. 1

    Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

    Published 2018
    “…It is also believed that the technique/s used while developing a model can impact the overall results. …”
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    Article
  2. 2

    Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

    Published 2018
    “…It is also believed that the technique/s used while developing a model can impact the overall results. …”
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    Article
  3. 3

    Urban green space spatio-temporal change influences on land surface temperature in Kuala Lumpur, Malaysia by Abu Kasim, Junainah

    Published 2020
    “…A linear regression technique was employed to investigate the correlation between both scenarios using spatial statistical analysis and further predicting the UGS pattern and LST gradient for 2025 using the Artificial Neural Network - Cellular Automaton (ANN-CA) model. …”
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    Thesis
  4. 4

    Finger Vein Recognition Using Pattern Map As Feature Extraction by Teoh, Saw Beng

    Published 2012
    “…Algorithms such as Gabor Filter, Local Line Binary Pattern (LLBP) and Principal Component Analysis (PCA) have been proposed in recent study to extract finger vein features. …”
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    Thesis
  5. 5

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

    Published 2015
    “…In this work, we will develop a robust classification model that can be utilized in cancer diagnosis using immunofingerprint data. …”
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    Proceeding Paper
  6. 6
  7. 7

    Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat by Mohammad Ahmad, Jomah Tubishat

    Published 2019
    “…Our results from the conducted experiments revealed that the proposed algorithm outperform the state-of-the-art aspect extraction algorithms and optimization algorithms. …”
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    Thesis
  8. 8

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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    Monograph
  9. 9

    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

    Published 2010
    “…In this paper, a two-stage pattern classification and rule extraction system is proposed. …”
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    Article
  10. 10

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

    Published 2020
    “…Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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    Final Year Project / Dissertation / Thesis
  11. 11
  12. 12

    Pattern discovery using k-means algorithm by Ahmed, Almahdi Mohammed, Wan Ishak, Wan Hussain, Md Norwawi, Norita, Alkilany, Ahmed

    Published 2014
    “…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
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    Conference or Workshop Item
  13. 13

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

    Published 2024
    “…Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. …”
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    Thesis
  14. 14

    Pattern Discovery Using K-Means Algorithm by Ahmed, AM, Norwawi, NM, Ishak, WHW, Alkilany, A

    Published 2024
    “…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
    Proceedings Paper
  15. 15

    Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

    Published 2005
    “…The primary concept of association rule algorithms consist of two phase procedure. In the first phase, all frequent patterns are found and the second phase uses these frequent patterns in order to generate all strong rules. …”
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    Thesis
  16. 16

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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    Final Year Project
  17. 17

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

    Published 2018
    “…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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    Thesis
  18. 18

    Neural Network Based Pattern Recognition in Visual Inspection System for Intergrated Circuit Mark Inspection by Sevamalai, Venantius Kumar

    Published 1998
    “…The feature extraction module was tested for its speed using various ROI sizes. …”
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    Thesis
  19. 19

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…As the components of big data continue to expand, the task of extracting useful information becomes critical. Topic extraction refers to the process of extracting main topics from the pool of news feed and a typical method to perform topic extraction is through clustering. …”
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    Article
  20. 20

    Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

    Published 2021
    “…The experimental results show that the ensemble method can improve the single classification model’s accuracy with the highest classification accuracy of 87.94% compared to the best single classification model. …”
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    Article