• Corpus ID: 198319474

Association Rule Development for Market Basket Dataset

@article{Bhaskar2018AssociationRD,
  title={Association Rule Development for Market Basket Dataset},
  author={Sachin Bhaskar},
  journal={International Journal of Computer Applications},
  year={2018},
  volume={180},
  pages={12-15}
}
  • S. Bhaskar
  • Published 15 June 2018
  • Computer Science
  • International Journal of Computer Applications
The Term Data mining is used to analyse a big dataset in Statistics. Data mining contains different kinds of approaches like classification, clustering and association. This research work focused on association rule only. association has two special characteristics, which are support and confidence. In this research work, the methodology of association has been studied and developed different rules for a real-life dataset of a super market. These rules are based on three items only. 

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References

SHOWING 1-10 OF 10 REFERENCES

A Study on Incremental Association Rule Mining

TLDR
The importance of incremental mining is elicited and various incremental mining algorithms that exist in the literature are discussed, which require much computational time and ignore the available mined knowledge.

ARAS: Efficient generation of Association Rules Using Antecedent Support

  • S. B. Bajaj
  • Computer Science
    2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)
  • 2014
TLDR
A novel approach named ARAS (Association Rule Using Antecedent Support) has been proposed for rule generation that uses memory resident data structure named FCET (Frequent Closed Enumeration Tree) to find frequent/closed itemsets.

Mining Positive and Negative Association Rules: An Approach for Confined Rules

TLDR
An algorithm is proposed that extends the support-confidence framework with sliding correlation coefficient threshold and discovers negative association rules with strong negative correlation between the antecedents and consequents.

Boosting association rule mining in large datasets via Gibbs sampling

TLDR
A Gibbs-sampling–induced stochastic search procedure to randomly sample association rules from the itemset space, and perform rule mining from the reduced transaction dataset generated by the sample is developed.

Association Rules Mining and Statistic Test over Multiple Datasets on TCM Drug Pairs

TLDR
An enhanced method to perform association rules mining over multiple databases to study the structural characters of TCM drug pairs and could get the only associations between drugs even those replicated property rules.

Concepts and Techniques

1 The Modern Microscope Today.- 2 The Quest for Ultra-High Resolution.- 3 Z-Contrast Imaging in the Scanning Transmission Electron Microscope.- 4 Inelastic Scattering in Electron Microscopy-Effects,

Data Mining - Concepts and Techniques

  • P. Perner
  • Computer Science
    Künstliche Intell.
  • 2002

Boosting association rule mining International Journal of Computer Applications

  • US National Library of Medicine National Institutes of health,
  • 2016

large datasets via Gibbs sampling, PubMed.gov, US National Library of Medicine National Institutes of health

  • 2016