NDLI: Unsupervised interaction-preserving discretization of multivariate data

Content Provider	Springer Nature Link
Author	Nguyen, Hoang Vu Müller, Emmanuel Vreeken, Jilles Böhm, Klemens
Copyright Year	2014
Abstract	Discretization is the transformation of continuous data into discrete bins. It is an important and general pre-processing technique, and a critical element of many data mining and data management tasks. The general goal is to obtain data that retains as much information in the continuous original as possible. In general, but in particular for exploratory tasks, a key open question is how to discretize multivariate data such that significant associations and patterns are preserved. That is exactly the problem we study in this paper. We propose IPD, an information-theoretic method for unsupervised discretization that focuses on preserving multivariate interactions. To this end, when discretizing a dimension, we consider the distribution of the data over all other dimensions. In particular, our method examines consecutive multivariate regions and combines them if (a) their multivariate data distributions are statistically similar, and (b) this merge reduces the MDL encoding cost. To assess the similarities, we propose $$ ID $$ , a novel interaction distance that does not require assuming a distribution and permits computation in closed form. We give an efficient algorithm for finding the optimal bin merge, as well as a fast well-performing heuristic. Empirical evaluation through pattern-based compression, outlier mining, and classification shows that by preserving interactions we consistently outperform the state of the art in both quality and speed.
Starting Page	1366
Ending Page	1397
Page Count	32
File Format	PDF
ISSN	13845810
Journal	Data Mining and Knowledge Discovery
Volume Number	28
Issue Number	5-6
e-ISSN	1573756X
Language	English
Publisher	Springer US
Publisher Date	2014-04-04
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Discretization Interaction preservation Pattern mining Outlier mining Classification Data Mining and Knowledge Discovery Artificial Intelligence (incl. Robotics) Information Storage and Retrieval Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Information Systems Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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