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  1. 1
    An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis

    An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis by Ong, Phaik Ling

    Published 2016
    “…However, frequent pattern mining (FPM) using Apriori-like algorithms and support-confidence framework suffers from the myth of rare item problem in nature. …”
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  2. 2
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  3. 3
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  4. 4
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  5. 5
    A Data Mining Approach For Developing Quality Prediction Model In Multi-Stage Manufacturing

    A Data Mining Approach For Developing Quality Prediction Model In Multi-Stage Manufacturing by Arif, Fahmi, Suryana, Nanna, Hussin, Burairah

    Published 2013
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  6. 6
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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  7. 7
    Evaluating integrated weight linear method to class imbalanced learning in video data

    Evaluating integrated weight linear method to class imbalanced learning in video data by Mohd Apandi, Ziti Fariha, Mustapha, Norwati, Affendey, Lilly Suriani

    Published 2011
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  8. 8
    Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction

    Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction by Sase, Takumi, Othman, Marini

    Published 2022
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  9. 9
    Prediction of ADHD from a small dataset using an adaptive EEG Theta/Beta Ratio and PCA feature extraction

    Prediction of ADHD from a small dataset using an adaptive EEG Theta/Beta Ratio and PCA feature extraction by Sase, Takumi, Othman, Marini

    Published 2022
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  10. 10
    A new model for iris data set classification based on linear support vector machine parameter's optimization

    A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

    Published 2020
    “…The SVM is a one technique of machine learning techniques that is well known technique, learning with supervised and have been applied perfectly to a vary problems of: regression, classification, and clustering in diverse domains such as gene expression, web text mining. In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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  11. 11
    Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques

    Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by AHMAD, IFTIKHAR

    Published 2011
    “…Instead of using traditional approach of selecting features with the highest eigenvalues such as PCA, this research applied a Genetic Algorithm (GA) to search the principal feature space that offers a subset of features with optimal sensitivity and the highest discriminatory power. …”
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  12. 12
    Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree

    Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree by Arowolo, Micheal Olaolu, Adebiyi, Marion Olubunmi, Adebiyi, Ayodele Ariyo

    Published 2021
    “…In this study, a novel optimized dimensionality reduction algorithm is proposed, by combining an optimized genetic algorithm with Principal Component Analysis and Independent Component Analysis (GA-O-PCA and GAO-ICA), which are used to identify an optimum subset and latent correlated features, respectively. …”
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  13. 13
    Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques

    Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by Iftikhar , Ahmad, Azween, Abdullah

    Published 2011
    “…Instead of using traditional approach of selecting features with the highest eigenvalues such as PCA, this research applied a Genetic Algorithm (GA) to search the principal feature space that offers a subset of features with optimal sensitivity and the highest discriminatory power. …”
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  14. 14
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Because of its widespread use in many applications, it remains an important and extensive research brand in data mining. …”
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  15. 15
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    “…Because of its widespread use in many applications, it remains an important and extensive research brand in data mining. …”
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  16. 16
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Because of its widespread use in many applications, it remains an important and extensive research brand in data mining. …”
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  17. 17
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Because of its widespread use in many applications, it remains an important and extensive research brand in data mining. …”
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  18. 18
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Because of its widespread use in many applications, it remains an important and extensive research brand in data mining. …”
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  19. 19
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

    Published 2023
    “…Because of its widespread use in many applications, it remains an important and extensive research brand in data mining. …”
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  20. 20
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

    Published 2023
    “…Because of its widespread use in many applications, it remains an important and extensive research brand in data mining. …”
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