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  1. 1
    Optimized feature construction methods for data summarizations of relational data

    Optimized feature construction methods for data summarizations of relational data by Sze, Florence Sia Fui

    Published 2014
    “…A classification task is commonly performed to discover frequent patterns in the data that can be used to classify new unknown data. …”
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    Thesis
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  2. 2
    A Data Mining Approach to Construct Graduates Employability Model in Malaysia

    A Data Mining Approach to Construct Graduates Employability Model in Malaysia by Myzatul Akmam Sapaat, Aida Mustapha, Johanna Ahmad, Khadijah Chamili, Rahamirzam Muhamad

    Published 2024
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  3. 3
    An efficient and effective case classification method based on slicing

    An efficient and effective case classification method based on slicing by Shiba, Omar A. A., Sulaiman, Md. Nasir, Mamat, Ali, Ahmad, Fatimah

    Published 2006
    “…The paper also discusses two of common classification algorithms that are used either in data mining or in general AI. …”
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  4. 4
    Knowledge base processing method based on text classification algorithm

    Knowledge base processing method based on text classification algorithm by Baisheng Zhong, Mohd Shamrie Sainin, Tan Soo Fun

    Published 2023
    “…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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  5. 5
    Ideal combination feature selection model for classification problem based on bio-inspired approach

    Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

    Published 2020
    “…Such a finding indicates that the exploitation of bio-inspired algorithms with ideal combination of wrapper/filtered method can contribute in finding the optimal features to be used in data mining model construction.…”
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    Book Section
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  6. 6
    An evolutionary based features construction methods for data summarization approach

    An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

    Published 2015
    “…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
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    Research Report
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  7. 7
    Optimization of attribute selection model using bio-inspired algorithms

    Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

    Published 2019
    “…Such a finding indicates that bio-inspired algorithms can contribute in identifying the few most important features to be used in data mining model construction.…”
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  8. 8
    Accuracy assessment of Digital Terrain Model (DTM) Constructed Cloth Simulation Filter (CSF) and Multi Curvature Classification (MCC) algorithm on UAV LiDAR dataset / Mohamad Khairan Mohd Asri

    Accuracy assessment of Digital Terrain Model (DTM) Constructed Cloth Simulation Filter (CSF) and Multi Curvature Classification (MCC) algorithm on UAV LiDAR dataset / Mohamad Khair... by Mohd Asri, Mohamad Khairan

    Published 2023
    “…Two algorithms, the Cloth Simulation Filter (CSF) in CloudCompare and the Multiscale Curvature Classification (MCC) in Global Mapper, were tested for this purpose. …”
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  9. 9
    Training data selection for record linkage classification

    Training data selection for record linkage classification by Zaturrawiah Ali Omar, Zamira Hasanah Zamzuri, Noratiqah Mohd Ariff, Mohd Aftar Abu Bakar

    Published 2023
    “…Random forest and support vector machine classification algorithms were compared, and random forest with the top and imbalanced construction produced an F1 -score comparable to probabilistic record linkage using the expectation maximisation algorithm and EpiLink. …”
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  10. 10
    Non-fiducial based electrocardiogram biometrics with kernel methods

    Non-fiducial based electrocardiogram biometrics with kernel methods by Hejazi, Maryamsadat

    Published 2017
    “…This approach constructs an algorithm by combining autocorrelation (AC) and Kernel Principal Component Analysis (KPCA) techniques. …”
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  11. 11
    An ensemble method with cost function on churn prediction

    An ensemble method with cost function on churn prediction by Mohd Khalid, Awang, Mohammad Afendee, Mohamed, Mokhairi, Makhtar

    Published 2019
    “…Therefore, this paper aims to achieve higher classification accuracy and at the same time, minimising ensemble classifiers by constructing a new ensemble method based on dimensionality reduction in soft set theory. …”
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  12. 12
    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

    “…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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    Monograph
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  13. 13
    Feature clustering for pso-based feature construction on high-dimensional data

    Feature clustering for pso-based feature construction on high-dimensional data by Swesi, Idheba Mohamad Ali Omer, Abu Bakar, Azuraliza

    Published 2019
    “…Hence, the ClusPSOFC method is effective for feature construction in the classification of high dimensional data.…”
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  14. 14
    Multi-label learning based on positive label correlations using predictive apriori

    Multi-label learning based on positive label correlations using predictive apriori by Al Azaidah, Raed Hasan Saleh

    Published 2019
    “…Along with that, two algorithms have been constructed by capturing the positive correlations where the first algorithm (MLR-PC) captures the positive global correlations and the second algorithm (MLCBA) proposes an adaption of AC algorithm to handle MLC based on the positive local correlations. …”
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  15. 15
    Machine learning for data classification in construction project planning

    Machine learning for data classification in construction project planning by Lau, Zheng Liang

    Published 2023
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    Final Year Project / Dissertation / Thesis
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  16. 16
    Classification with degree of importance of attributes for stock market data mining

    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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  17. 17
    Deep learning for EEG data analysis

    Deep learning for EEG data analysis by Cheah, Kit Hwa

    Published 2018
    “…The convolutional neural network (CNN) model constructed in this project has achieved a validation accuracy of 75±1% using the same EEG dataset. …”
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    Final Year Project / Dissertation / Thesis
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  18. 18
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
    thesis::doctoral thesis
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  19. 19
    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…As for EMG feature selection, the proposed algorithms are evaluated using the EMG data acquired from the publicly access EMG database. …”
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  20. 20
    Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization

    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
    “…Identifying a feature selection method with a classifier algorithm that produces high performance in mortality studies is essential and has not been reported before. …”
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