A comparative analysis of tools for visualizing association rules: A proposal for visualising fuzzy association rules

被引：0

作者：

Fernandez-Basso, Carlos ^{[1
]}

Dolores Ruiz, M. ^{[1
]}

Delgado, Miguel ^{[1
]}

Martin-Bautista, Maria J. ^{[1
]}

机构：

[1] Univ Granada, CITIC UGR, Comp Sci & AI Dept, Granada, Spain

来源：

PROCEEDINGS OF THE 11TH CONFERENCE OF THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY (EUSFLAT 2019) | 2019年 / 1卷

基金：

欧盟地平线“2020”;

关键词：

Association Rules; Fuzzy Association Rules; Visualization; Frequent item-sets mining; Data Mining; SEQUENTIAL PATTERNS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Discovering new trends and co-occurrences in massive data is a key step when analysing social media, data coming from sensors, etc. Although, nowadays Data Mining is very useful and widely used for the industry, business and government, the main problem of application of machine learning or data mining in other fields is the interpretability and complexity of obtained results for non-expert users in computer or data science. For this reason in the KDD process one of the most important phases is the interpretation and evaluation. In the case of association rules is essential that results are interpretable for experts. One of the most useful tools for this goal is the visualization, because it clarifies the interpretation of results, being easier to understand in order to take a decision or explaining the behaviour of data.

引用

页码：520 / 527

页数：8