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  1. 1
    Logistic regression methods for classification of imbalanced data sets

    Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

    Published 2012
    “…Hence, it is required to develop effective imbalanced LR-based methods to be widely used in data mining applications. …”
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  2. 2
    Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan

    Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan by Aznan, Muhammad Nur Syazwanie Aznan

    Published 2019
    “…Which is why this project objective is to develop a web based clustering tool using K-MEAN++ algorithm. …”
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  3. 3
    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…The increasing size of data being stored have created the need for computer-based methods for automatic data analysis. Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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  4. 4
    Development Of Analytical Solution For Thermo-Mechanical Stresses Of Multilayered Pressure Vessel Based On Recursive Algorithm

    Development Of Analytical Solution For Thermo-Mechanical Stresses Of Multilayered Pressure Vessel Based On Recursive Algorithm by Sim, Lih Chi

    Published 2022
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  5. 5
    Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment

    Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S.

    Published 2024
    “…The leakage fault cases verify the algorithm�s applicability and complete the correlation diagnosis of water wall leakage fault. …”
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  6. 6
    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data

    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

    Published 2024
    “…The comparison analysis exhibits that our suggested approach outperforms the others, especially for computational time. The developed approach is benchmarked with the existing methods such as MiniBatchKmeans, AffinityPropagation, SpectralClustering, Ward, OPTICS, and BRICH in terms of silhouette index and cost function.…”
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  7. 7
    Density subspace clustering: a case study on perception of the required skill

    Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

    Published 2014
    “…DAMIRA successfully clustered all of the data, while INSCY method has a lower coverage than FIRES method. For F1 Measure, SUBCLU method is better than FIRES, INSCY, and DAMIRA. …”
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  8. 8
    Application of Optimization Methods for Solving Clustering and Classification Problems

    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…This method does not explicitly use derivatives, and is particularly appropriate when functions are non-smooth. …”
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  9. 9
    Design and evaluation on adaptive fuzzy speed control of mobile robot

    Design and evaluation on adaptive fuzzy speed control of mobile robot by Abdollahi, Mohammadreza

    Published 2011
    “…Both data acquisition and control algorithm are developed by using LabVIEW. A four-wheel mobile robot, PUTRABOT2, is used to conduct the experiments. …”
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  10. 10
    Application of target detection method based on convolutional neural network in sustainable outdoor education

    Application of target detection method based on convolutional neural network in sustainable outdoor education by Yang, Xiaoming, Samsudin, Shamsulariffin, Wang, Yuxuan, Yuan, Yubin, Tengku Kamalden, Tengku Fadilah, Yaakob, Sam Shor Nahar

    Published 2023
    “…Different recognition methods have certain advantages in accuracy, speed, and other aspects. …”
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  11. 11
    Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis

    Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis by Abujayyab, Sohaib K. M.

    Published 2017
    “…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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  12. 12
    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…Overall, this study offers new insights into remote sensing urban applications, specifically for roof-based mapping through the development of systematic improvement approach using OBIA. …”
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  13. 13
    Integrated framework with association analysis for gene selection in microarray data classification

    Integrated framework with association analysis for gene selection in microarray data classification by Ong, Huey Fang

    Published 2011
    “…To achieve that, an integrated framework with a new gene selection method was developed to improve classification performance in terms of accuracy and number of selected genes. …”
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  14. 14
    Modifying iEclat algorithm for infrequent patterns mining

    Modifying iEclat algorithm for infrequent patterns mining by Julaily Aida, J., Mustafa, M.

    Published 2018
    “…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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    Conference or Workshop Item
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  15. 15
    Efficient prime-based method for interactive mining of frequent patterns.

    Efficient prime-based method for interactive mining of frequent patterns. by Mohammad Hossein, Nadimi Shahraki, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2011
    “…Since rerunning mining algorithms from scratch is very costly and time-consuming, researchers have introduced interactive mining of frequent patterns. …”
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  16. 16
    Machine learning application in predicting anterior cruciate ligament injury among basketball players

    Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

    Published 2025
    “…Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. …”
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  17. 17
    Web user navigation pattern mining approach based on graph partitioning algorithm.

    Web user navigation pattern mining approach based on graph partitioning algorithm. by Jalali, Mehrdad, Mustapha, Norwati, Mamat, Ali, Sulaiman, Md. Nasir

    Published 2008
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  18. 18
    Modifying iEclat algo ithm for infrequent patterns mining

    Modifying iEclat algo ithm for infrequent patterns mining by Julaily Aida, Jusoh, Mustafa, Man

    Published 2018
    “…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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  19. 19
    Prime-based method for interactive mining of frequent patterns

    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Moreover, this study introduces a mining algorithm called PC-miner to mine the mining model frequently with various values of minsup. …”
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  20. 20
    A web usage mining approach based on LCS algorithm in online predicting recommendation systems

    A web usage mining approach based on LCS algorithm in online predicting recommendation systems by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2008
    “…To provide online prediction efficiently, we advance an architecture for online predicting in Web Usage Mining system and propose a novel approach based on LCS algorithm for classifying user navigation patterns for predicting users' future requests. …”
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