Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Videos
Videos
Thesis submission
Thesis submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Contact us
Contact us
StreamMARS: A Streaming Multivariate Adaptive Regression Splines Algorithm
Date
2019-12-14
Author
BATMAZ, İNCİ
ADAMS, NIALL
Metadata
Show full item record
Item Usage Stats
11
views
0
downloads
Cite This
Computers and internet have become inevitable parts of our life in the 1990s, and afterwards, bulk of data are started being recorded in digital platforms automatically. To extract meaningful patterns from such data computational methods are developed in data mining and machine learning domains. Multivariate adaptive regression splines (MARS) is one such method successfully applied to off-line static data for prediction. In about last ten years, we face with the big data problem due to the steady increase in the size of the data. Streaming data is a kind of big data collected from sensor networks, production processes, twitter messages etc. Algorithms processing this type of data should consider both memory and time limitations as well as its changing nature with time. We develop a streaming version of a powerful predictive method MARS for estimating model parameters on-line in a temporarily adaptive manner using forgetting factors. Performance of the algorithm developed is tested on simulated data with different dimensions in static, abrupt and smoothly changing environments; as well as on real-life datasets, and also, compared with those of some benchmarking methods such as sliding windows. Results show that StreamMARS is a promising algorithm for predicting streaming big data.
URI
https://hdl.handle.net/11511/72160
http://www.cmstatistics.org/RegistrationsV2/CFE2019/viewSubmission.php?in=361&token=630norqsrrr6190q2775p452ro88938n
http://www.cmstatistics.org/CMStatistics2019/fullprogramme.php
http://www.cfenetwork.org/CFE2019/docs/BoACFECMStatistics2019.pdf?20191121220051
Collections
Department of Statistics, Conference / Seminar
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
İ. BATMAZ and N. ADAMS, “StreamMARS: A Streaming Multivariate Adaptive Regression Splines Algorithm,” London, UK, 2019, p. 71, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/72160.