2015 3rd International Conference on Information and Communication Technology (ICoICT) 2015
DOI: 10.1109/icoict.2015.7231419
|View full text |Cite
|
Sign up to set email alerts
|

Dimensionality reduction for association rule mining with IST-EFP algorithm

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2016
2016
2024
2024

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 6 publications
(1 citation statement)
references
References 4 publications
0
1
0
Order By: Relevance
“…The principal component analysis (PCA) is integrated in the proposed model as a preprocessing stage followed by the utilization of the a priori algorithm for association rule (strategy map) discovery. In this sense, PCA is used for dimensionality reduction in order to discover association rules (Siswanto, 2018).…”
Section: Principal Component Analysis In Formation Of Association Rules Applied To Identify the Relationships Structure Of Advantages Andmentioning
confidence: 99%
“…The principal component analysis (PCA) is integrated in the proposed model as a preprocessing stage followed by the utilization of the a priori algorithm for association rule (strategy map) discovery. In this sense, PCA is used for dimensionality reduction in order to discover association rules (Siswanto, 2018).…”
Section: Principal Component Analysis In Formation Of Association Rules Applied To Identify the Relationships Structure Of Advantages Andmentioning
confidence: 99%