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  1. 1
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2009
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  2. 2
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2008
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  3. 3
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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  4. 4
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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  5. 5
    Frequent patterns minning of stock data using hybrid clustering association algorithm

    Frequent patterns minning of stock data using hybrid clustering association algorithm by B., Baharudin, A., Khan, K., Khan

    Published 2009
    “…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data. …”
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  6. 6
    Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering

    Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering by Rahmah, Mokhtar, Raza, Muhammad Ahsan, Fauziah, Zainuddin, Nor Azhar, Ahmad, Raza, Muhammad Fahad, Raza, Binish

    Published 2021
    “…In this paper, we have compared the performance of K-Mean and XMean clustering algorithms using two datasets of student enrollment in higher education institutions. …”
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  7. 7
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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  8. 8
    Pattern Discovery Using K-Means Algorithm

    Pattern Discovery Using K-Means Algorithm by Ahmed, AM, Norwawi, NM, Ishak, WHW, Alkilany, A

    Published 2024
    “…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
    Proceedings Paper
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  9. 9
    Clustering of rainfall data using k-means algorithm

    Clustering of rainfall data using k-means algorithm by Mohd Sham, Mohamad, Yuhani, Yusof, Ku Muhammad Na’im, Ku Khalif, Mohd Khairul Bazli, Mohd Aziz

    Published 2019
    “…K-Means algorithm is used to obtain optimal rainfall clusters. …”
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  10. 10
    Modeling of vehicle trajectory using K-means and fuzzy C-means clustering

    Modeling of vehicle trajectory using K-means and fuzzy C-means clustering by Choong, Mei Yeen, Lorita Angeline, Chin, Renee Ka Yin, Yeo, Kiam Beng, Teo, Kenneth Tze Kin

    Published 2019
    “…However, it will be a tremendous work for traffic operators to observe the vehicle flows manually where thousands of vehicles may travel through an intersection. Hence, the clustering of vehicle trajectory dataset for similar patterns identification is implemented with k-means and fuzzy c-means (FCM) clustering algorithm. …”
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  11. 11
    A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques

    A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques by Sharifah Sakinah, Syed Ahmad

    Published 2014
    “…Clustering analysis has been considered as a useful means for identifying patterns in dataset. …”
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  12. 12
    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

    Published 2011
    “…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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  13. 13
    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, Khan

    Published 2011
    “…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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  14. 14
    A modified π rough k-means algorithm for web page recommendation system

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

    Published 2018
    “…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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  15. 15
    Customer segmentation on clustering algorithms

    Customer segmentation on clustering algorithms by Toh, Wei Xuan

    Published 2023
    “…This report presents an analysis of customer segmentation using various clustering algorithms, including k-means, DBSCAN, GMM, and RFM. …”
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  16. 16
    Pattern discovery using k-means algorithm

    Pattern discovery using k-means algorithm by Ahmed, Almahdi Mohammed, Wan Ishak, Wan Hussain, Md Norwawi, Norita, Alkilany, Ahmed

    Published 2014
    “…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
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  17. 17
    Pattern Classification of Human Epithelial Images

    Pattern Classification of Human Epithelial Images by Mohd Isa, Mohd Fazlie

    Published 2016
    “…Last but not least, from the mean of properties, it will classify into the pattern after ranging the value of mean properties of each of the pattern itself that has been done in classification stage.…”
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  18. 18
    Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images

    Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images by Jabar F.H.A., Ismail W., Salam R.A., Hassan R.

    Published 2024
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  19. 19
    Social media mining: a genetic based multiobjective clustering approach to topic modelling

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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  20. 20
    Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data

    Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data by Laxmi Lydia E., Sharmili N., Nguyen P.T., Hashim W., Maseleno A.

    Published 2023
    “…Automatic indexing; Big data; Cluster analysis; Extraction; Factorization; Indexing (of information); Information retrieval; K-means clustering; Natural language processing systems; Open source software; Open systems; Pattern matching; Software quality; Software testing; Text mining; Hadoop; Key phrase extractions; Map-reduce; Pattern-matching technique; Porters; Pre-processing algorithms; Software environments; Unlabeled; Matrix algebra…”
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