A Study of Predictive Accuracy for Four Associative Classifiers

Keywords

Associative property, Pruning, Benchmark (surveying), Computer science, Association rule learning

References

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Cited by

• A geographic knowledge discovery approach to property valuationK. Christopoulou — 2009
• A comparative study of four feature selection methods for associative classifiersKavita Das, O. P. Vyas — 2010
• Compact fuzzy association rule-based classifierFerenc Péter Pach, Attila Gyenesei, János Abonyi — 2008
• Distributed fuzzy rule miner (DFRM)Samane Sharif, Mohammad Reza Akbarzadeh-T — 2013
• CPPA: A Fast Coverage AlgorithmPhung Trung Nghia, Phạm Việt Bình, Nguyen Huu Thai — 2007
• Association Rule Mining with Dynamic Adaptive Support Thresholds for Associative ClassificationSunil Surve, Niharika Singh, B. K. Lande — 2007
• A Suitability Study of Discretization Methods for Associative ClassifiersKavita Das, O. P. Vyas — 2010
• CSMC: A combination strategy for multi-class classification based on multiple association rulesYezheng Liu, Yuanchun Jiang, Xiao Liu — 2008
• Data Analytics Tools: A User PerspectivePaul Town, Fadi Thabtah — 2019
• Sport analytics for cricket game results using machine learning: An experimental studyKumash Kapadia, Hussein Abdel-Jaber, Fadi Thabtah — 2020
• Generalization Driven Fuzzy Classification Rules Extraction using OLAM Data CubesRaghuram Bhukya — 2020
• Emerging Trends in Associative Classification Data MiningNeda Abdelhamid, Aladdin Ayesh, Fadi Thabtah — 2014
• Constructing Associative Classifier Using Rough Sets and Evidence TheoryYuanchun Jiang, Ye-Zheng Liu, X. Liu — 2009
• An Efficient Associative Classification Algorithm for Text CategorizationBashar A Suleiman, Abdallah Aburumman, Fadi Fayez Abdel-jaber — 2013
• CMARPGA: Classification Based on Multiple Association Rules Using Parallel Genetic Algorithm Pruned Decision TreeHanChern-Tong, I. Aziz — 2017

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