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  1. 1

    A recommender system approach for classifying user navigation patterns using longest common subsequence algorithm. by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2009
    “…The approach is based on the using longest common subsequence algorithm to classify current user activities to predict user next movement. …”
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    Article
  2. 2

    Comparison Performance of Qualitative Bankruptcy Classification based on Data Mining Algorithms by Nilam Nur Amir, Sjarif, Yee, Fang Lim, NurulHuda, Mohd Firdaus Azmi, Kamalia, Kamardin, Doris Wong, Hooi Ten, Hafiza, Abas, Mubarak-Ali, Al-Fahim

    Published 2018
    “…This paper presents a comparison of three different classification algorithms namely NaiveBayes (NaiveBayes classifier), Logistic Regression (Logistic classifier) and C4.5 decision tree (J48 classifier) for bankruptcy classification analysis. …”
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    Article
  3. 3

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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    Thesis
  4. 4

    Performance analysis of feature selection algorithm for educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

    Published 2018
    “…Feature Selection (FS) algorithms remove irrelevant data from the educational dataset and hence increases the performance of classifiers used in EDM techniques. …”
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    Article
  5. 5

    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

    Published 2021
    “…A classifier model is developed using Naive Bayes characteristics. …”
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    Thesis
  6. 6

    Using fuzzy association rule mining in cancer classification by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

    Published 2011
    “…At first, different subset of genes which have been selected by different methods, were used to generate primary fuzzy classifiers separately and then proposed algorithm was implemented to mix the genes which have been associated in the primary classifiers and generate a new classifier. …”
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    Article
  7. 7
  8. 8

    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

    Published 2017
    “…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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    Thesis
  9. 9

    Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

    Published 2025
    “…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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    Final Year Project / Dissertation / Thesis
  10. 10

    A direct ensemble classifier for imbalanced multiclass learning by Sainin, Mohd Shamrie, Alfred, Rayner

    Published 2012
    “…Researchers have shown that although traditional direct classifier algorithm can be easily applied to multiclass classification, the performance of a single classifier is decreased with the existence of imbalance data in multiclass classification tasks.Thus, ensemble of classifiers has emerged as one of the hot topics in multiclass classification tasks for imbalance problem for data mining and machine learning domain.Ensemble learning is an effective technique that has increasingly been adopted to combine multiple learning algorithms to improve overall prediction accuraciesand may outperform any single sophisticated classifiers.In this paper, an ensemble learner called a Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML) that combines simple nearest neighbour and Naive Bayes algorithms is proposed. …”
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    Conference or Workshop Item
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    Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach by Munnian, Ruthrakumar

    Published 2019
    “…Classification analysis was initially performed on all seven classifier’s algorithms at 10-fold dross validation mode. …”
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    Monograph
  13. 13

    Hybrid ant colony optimization and genetic algorithm for rule induction by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…The AntMiner classifier is efficient, useful and commonly used for solving rulebased classification problems in data mining. …”
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    Article
  14. 14

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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  15. 15

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

    Published 2016
    “…Among all these techniques, classification is one of the most commonly used tasks in data mining, which is used by many researchers to classify instances into two or more pre-determined classes. …”
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    Thesis
  16. 16

    A novel approach to data mining using simplified swarm optimization by Wahid, Noorhaniza

    Published 2011
    “…In this thesis, a novel Simplified Swarm Optimization (SSO) algorithm is proposed as a rule-based classifier and for feature selection. …”
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    Thesis
  17. 17

    A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining by Jalali, Mehrdad

    Published 2009
    “…In the online phase, the longest common subsequence algorithm is used as a new approach in recommendation system for classifying current user activities to predict user next movements. …”
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    Thesis
  18. 18

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…This research has proven that the TIP method has shown the ability to cater for different kinds of datasets and obtained a good rough classification model with promising results as compared with other commonly used classifiers. This research opens a wide range of future work to be considered, which includes applying the proposed method in other areas such as web mining, text mining or multimedia mining; and extending the proposed approach to work in parallel computing in data mining.…”
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    Thesis
  19. 19

    Advanced data mining techniques for landslide susceptibility mapping by Ibrahim, M.B., Mustaffa, Z., Balogun, A.-L., Hamonangan Harahap, I.S., Ali Khan, M.

    Published 2021
    “…SVM, RT, and NBM algorithms were used to produce predicted datasets from the training datasets. …”
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  20. 20

    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
    “…This huge amount of data can be a useful source of knowledge. Advanced mining processes are needed for this knowledge to be extracted, understood and used. …”
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    Article