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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

    Published 2018
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  5. 5
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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    Conference or Workshop Item
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  6. 6
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  7. 7
    A Multi-tier Model and Filtering Approach to Detect Fake News Using Machine Learning Algorithms

    A Multi-tier Model and Filtering Approach to Detect Fake News Using Machine Learning Algorithms by Yu, Chiung Chang, A Hamid, Isredza Rahmi, Abdullah, Zubaile, Kipli, Kuryati, Amnur, Hidra

    Published 2024
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  8. 8
    A Voting Technique Of Multilayer Perceptron Ensemble For Classification Application

    A Voting Technique Of Multilayer Perceptron Ensemble For Classification Application by Talib, Hafizah

    Published 2014
    “…The instability of MLP performance where small changes in training parameter could produce different models that inhibiting attainment of high accuracy in classification applications. …”
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  9. 9
    Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique

    Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique by Jais, Fatin Nabihah, Che Azemin, Mohd Zulfaezal, Hilmi, Mohd Radzi, Mohd Tamrin, Mohd Izzuddin, Mohd. Kamal, Khairidzan

    Published 2021
    “…Conclusion. Machine learning algorithms can produce a highly accurate postsurgery classification model of BCVA changes using pterygium characteristics.…”
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  10. 10
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  11. 11
    Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun

    Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun by Mohammad Harun, Muhammad Firdaus

    Published 2019
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  12. 12
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…Algorithmic level based methods however are based on introducing new optimization task to improve the minority class classification rate, without changing the data characteristics. …”
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  13. 13
    Fusion of moment invariant method and deep learning algorithm for COVID-19 classification

    Fusion of moment invariant method and deep learning algorithm for COVID-19 classification by Ervin Gubin Moung, Chong, Joon Hou, Maisarah Mohd Sufian, Mohd Hanafi Ahmad Hijazi, Jamal Ahmad Dargham, Sigeru Omatu

    Published 2021
    “…This paper proposes a fusion of a moment invariant (MI) method and a DL algorithm for feature extraction to address the instabilities in the existing COVID-19 classification models. …”
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  14. 14
    Rule-based embedded HMMs phoneme classification to improve Qur’anic recitation recognition

    Rule-based embedded HMMs phoneme classification to improve Qur’anic recitation recognition by Mohammed Ali Alqadasi, Ammar, Sunar, Mohd Shahrizal, Turaev, Sherzod, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Salam, Md Sah, Alashbi, Abdulaziz Ali Saleh, Ahmed Salem, Ali, Ali, Mohammed A. H.

    Published 2022
    “…This paper introduces a Rule-Based Phoneme Duration Algorithm to improve phoneme classification in Qur’anic recitation. …”
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  15. 15
    Hybrid signal processing and machine learning algorithm for adaptive fault classification of wind farm integrated transmision line protection

    Hybrid signal processing and machine learning algorithm for adaptive fault classification of wind farm integrated transmision line protection by Olufemi, Osaji Emmanuel, Othman, Mohammad Lutfi, Hizam, Hashim, Othman, Muhammad Murtadha, Ammar, Aker Elhadi Emhemed Alhaaj, Okeke, Chidiebere Akachukwu, Onuabuchi, Nwagbara Samuel

    Published 2019
    “…The supervised machine learning algorithm from Bayesian network classified 99.15 % faults correctly with the operation time of 0.01 s to produced best-generalized model with an RMS error value of 0.05 for single line-to-ground (SLG) fault identification and classification. …”
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  16. 16
    Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation

    Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation by Pande C.B., Srivastava A., Moharir K.N., Radwan N., Mohd Sidek L., Alshehri F., Pal S.C., Tolche A.D., Zhran M.

    Published 2025
    “…The present investigation further enabled the interpretation of pixel-level LULC interactions while improving image classification accuracy and suggested the best models for the classification of LULC maps through the identification of changes in LULC classes. ? …”
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  17. 17
    Hyper-heuristic framework for sequential semi-supervised classification based on core clustering

    Hyper-heuristic framework for sequential semi-supervised classification based on core clustering by Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim

    Published 2020
    “…We designated this model as hyper-heuristic framework for semi-supervised classification or HH-F. …”
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  18. 18
    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan C.H., Tan M.S., Chang S.-W., Yap K.S., Yap H.J., Wong S.Y.

    Published 2023
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  19. 19
    Analysing the performance of classification algorithms on diseases datasets

    Analysing the performance of classification algorithms on diseases datasets by Lydia E.L., Sharmil N., Shankar K., Maseleno A.

    Published 2023
    “…The proposed classification algorithms measure the diseases using the disease datasets which estimates the accurate prediction. …”
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  20. 20
    Autism spectrum self-stimulatory behaviours classification using explainable temporal coherency deep networks and SVM classifier / Liang Shuaibing

    Autism spectrum self-stimulatory behaviours classification using explainable temporal coherency deep networks and SVM classifier / Liang Shuaibing by Liang , Shuaibing

    Published 2022
    “…Meanwhile, it is often difficult to obtain good classification results using unlabelled data, further research to train a model that can obtain good classification results and at the same time being practical will be valuable. …”
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