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Работы, на которые ссылается эта работа

Работ: 32

Работа: Distance based clustering of class association rules to build a compact, accurate and descriptive classifier

  1. A new approach to classification based on association rule mining

    Guoqing Chen, Hongyan Liu, Yu Lan +2

    Статья2005Цитирований: 7
    ABI

  2. CBC: An associative classifier with a small number of rules

    Houtao Deng, George C. Runger, Eugene Tuv +1

    Статья2013Цитирований: 6
    ABI

  3. C4.5: Programs for Machine Learning

    J. R. Quinlan

    Книга1992Цитирований: 6
    ABI

  4. Building an associative classifier with multiple minimum supports

    Li-Yu Hu, Ya‐Han Hu, Chih‐Fong Tsai +2

    Статья2016Цитирований: 6
    ABI

  5. Simple and Accurate Classification Method Based on Class Association Rules Performs Well on Well-Known Datasets

    Jamolbek Mattiev, Branko Kavšek

    Глава2019Цитирований: 6
    ABI

  6. UCI Machine Learning Repository

    Arthur Asuncion

    Статья2007Цитирований: 6
    ABI

  7. Integrating classification and association rule mining

    Bing Liu, Wynne Hsu, Yiming Ma

    Статья1998Цитирований: 5
    ABI

  8. New Associative Classification Method Based on Rule Pruning for Classification of Datasets

    Khairan Rajab

    Статья2019Цитирований: 5
    ABI

  9. A comparative study of clustering methods

    Mohamed Zaït, Hammou Messatfa

    Статья1997Цитирований: 5
    ABI

  10. Classification of association rules based on K-means algorithm

    Azzeddine Dahbi, Mohamed Mouhir, Youssef Balouki +1

    Статья2016Цитирований: 5
    ABI

  11. A compact and understandable associative classifier based on overall coverage

    Jamolbek Mattiev, Branko Kavšek

    Статья2020Цитирований: 5
    ABI

  12. Fast algorithms for mining association rules

    Rakesh Agrawal, Ramakrishnan Srikant

    Статья1998Цитирований: 4
    ABI

  13. MMAC: A New Multi-Class, Multi-Label Associative Classification Approach

    Fadi Thabtah, Peter Cowling, Yonghong Peng

    Статья2005Цитирований: 4
    ABI

  14. MCAR: multi-class classification based on association rule

    Fadi Thabtah, Peter Cowling, Yonghong Peng

    Статья2005Цитирований: 4
    ABI

  15. FURIA: an algorithm for unordered fuzzy rule induction

    Jens Hühn, Eyke Hüllermeier

    Статья2009Цитирований: 4
    ABI

  16. Efficient and Effective Clustering Methods for Spatial Data Mining

    Raymond T. Ng, Jiawei Han

    Статья1994Цитирований: 4
    ABI

  17. Distance based clustering of association rules

    Gunjan Gupta, Alexander L. Strehl, Joydeep Ghosh

    Статья1999Цитирований: 4
    ABI

  18. Mining Clusters with Association Rules

    Walter A. Kosters, Elena Marchiori, Ard Oerlemans

    Глава1999Цитирований: 4
    ABI

  19. Combining Naive Bayes and Decision Tables

    Mark A. Hall, Eibe Frank

    Статья2008Цитирований: 3
    ABI

  20. An Optimized Associative Classifier for Incremental Data Based On Non-Trivial Data Insertion

    R. Ramesh, V. Saravanan, R. Manikandan

    Статья2019Цитирований: 3
    ABI

  21. Generating Accurate Rule Sets Without Global Optimization

    Eibe Frank, Ian H. Witten

    Статья1998Цитирований: 3
    ABI

  22. AN OVERVIEW OF COMBINATORIAL DATA ANALYSIS

    Phipps Arabie, Lawrence J. Hubert

    Глава1996Цитирований: 3
    ABI

  23. Fast Effective Rule Induction

    William W. Cohen

    Глава1995Цитирований: 3
    ABI

  24. Clustering association rules

    Brian Lent, A. Swami, Jennifer Widom

    Статья2002Цитирований: 3
    ABI

  25. Pruning and Grouping Discovered Association Rules

    Hannu Toivonen, Mika Klemettinen, P. Ronkainen +2

    Статья1995Цитирований: 2
    ABI