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  1. 1

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The experimental results demonstrate that the proposed algorithm is competitive compared to the state-of-the-art semi-supervised learning algorithms in terms of accuracy. …”
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    Thesis
  2. 2

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…Initiating clustering from scratch in each time-bin and not considering the relationships between the objects from two consecutive time-bins lead to creating redundant micro clusters centralizes in the border area between two adjacent time bins. …”
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  3. 3

    Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System by Hormozi, Shahram Golzari

    Published 2011
    “…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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  4. 4
  5. 5

    Detection on ambiguous software requirements specification written in malay using machine learning by Zahrin, Mohd Firdaus

    Published 2017
    “…Four (4) algorithms have been evaluated to find the suitable classification algorithm for this purpose. …”
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  6. 6

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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  7. 7

    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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    Article
  8. 8

    Combining cluster quality index and supervised learning to predict students’ academic performance by Suhaila Zainudin, Rapi’ah Ibrahim, Hafiz Mohd Sarim

    Published 2024
    “…Three classification algorithms have been selected: Logistic Regression (LR), Support Vector Machine (SVM) and Decision Tree (DT). …”
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  9. 9

    Comparative study of apriori-variant algorithms by Mutalib, Sofianita, Abdul Subar, Ammar Azri, Abdul Rahman, Shuzlina, Mohamed, Azlinah

    Published 2016
    “…However, the algorithm suffers from scanning time problem while generating candidates of frequent itemsets.This study presents a comparative study between several Apriori-variant algorithms and examines their scanning time.We performed experiments using several sets of different transactional data.The result shows that the improved Apriori algorithm manage to produce itemsets faster than the original Apriori algorithm.…”
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    Conference or Workshop Item
  10. 10

    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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    Article
  11. 11

    A modified π rough k-means algorithm for web page recommendation system by Zidane, Khaled Ali Othman

    Published 2018
    “…The experimental results revealed that the modified πRKM algorithm performed better than the previous version in terms of the correct identification of overlapping objects between positive clusters. …”
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  12. 12

    Satisfiable Integer Programming Algorithm On Distributed Inter Process Communication (SIP-DIPC) by Abdul Hamid, Mohd Hakim, Abu, Nur Azman, Mohamad, Siti Nurul Mahfuzah, Idris, Aris, Zakaria, Zahriladha, Sulaiman, Zuraidah

    Published 2019
    “…Data Analytics is a superset to Data Mining. Data mining algorithm is getting popular support in recent development of Big Data. …”
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  13. 13

    RARE: mining colossal closed itemset in high dimensional data by Md Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza

    Published 2018
    “…The task of mining association rules highly relies on the efficiency of the algorithms to extract all frequent itemsets that exist in the database. …”
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  14. 14

    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. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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  15. 15

    Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

    Published 2022
    “…On the other hand, traditional machine learning algorithms (ML) that are based on manually extracted features are considered tedious and time dunting, as Arabic language contains multiple dialects and no word-based order. …”
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  16. 16

    An automated learner for extracting new ontology relations by Amaal Saleh Hassan, Al Hashimy, Narayanan, Kulathuramaiyer

    Published 2013
    “…Also we present a novel approach of learning based on the best lexical patterns extracted, besides two new algorithms the CIA and PS that provide the final set of rules for mining causation to enrich ontologies.…”
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  17. 17

    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
    “…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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  19. 19

    An association rule mining approach in predicting flood areas by Mokhairi, Makhtar, Nur Ashikin, Harun, Azwa, Abdul Aziz, Zahrahtul Amani, Zakaria, Engku Fadzli Hasan, Syed Abdullah, Julaily Aida, Jusoh

    Published 2017
    “…The association rules mining technique will generate the best rules from the dataset by using Apriori algorithm which had been applied to find the frequent itemsets. …”
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    Conference or Workshop Item
  20. 20

    Time series data intelligent clustering algorithm for landslide displacement prediction by Han, Liu, Shang, Tao, Shu, Jisen, Khan Chowdhury, Ahmed Jalal

    Published 2018
    “…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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