The Library
Data mining and compression : where to apply it and what are the effects?
Tools
Tools
Tools
Taylor, Phillip M., Griffiths, Nathan, Xu, Zhou and Mouzakitis, Alexandros (2019) Data mining and compression : where to apply it and what are the effects? In: 8th SIGKDD International Workshop on Urban Computing, Anchorage, Alaska , 5 Aug 2019. Published in: Proceedings of the 8th SIGKDD International Workshop on Urban Computing doi:10.1145/1122445.1122456
|
PDF
WRAP-data-mining-compression-effects-Taylor-2019.pdf - Accepted Version - Requires a PDF viewer. Download (1089Kb) | Preview |
Official URL: https://doi.org/10.1145/1122445.1122456
Abstract
In data mining it is important for any transforms made to training
data to be replicated on evaluation or deployment data. If they
is not, the model may perform poorly or be unable to accept the
input. Lossy data compression has other considerations, however,
for example it may not be known whether or not lossy compression
will be applied to deployment data, or if a variable compression
ratio is to be used. Furthermore, lossy data compression typically
reduces noise, which may not affect or even improve model performances, and performing feature selection on lossy data may
find better features than selecting from the original data. In this
paper, we investigate the effects of selecting features, learning, and
making predictions from data that has been compressed using lossy
transforms. Using vehicle telemetry data, we determine where in
the data mining methodology lossy compression is detrimental
or beneficial, and how it should be compressed. We also propose
a specialised feature selection approach that considers predictive
performance alongside compressibility, measured by compressing
them either individually or in a single concatenated stream
| Item Type: | Conference Item (Paper) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | |||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | |||||||||
| Library of Congress Subject Headings (LCSH): | Data mining, Data compression (Computer science) , Machine theory | |||||||||
| Journal or Publication Title: | Proceedings of the 8th SIGKDD International Workshop on Urban Computing | |||||||||
| Publisher: | ACM | |||||||||
| Official Date: | 5 August 2019 | |||||||||
| Dates: |
|
|||||||||
| DOI: | 10.1145/1122445.1122456 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||
| RIOXX Funder/Project Grant: |
|
|||||||||
| Conference Paper Type: | Paper | |||||||||
| Title of Event: | 8th SIGKDD International Workshop on Urban Computing | |||||||||
| Type of Event: | Conference | |||||||||
| Location of Event: | Anchorage, Alaska | |||||||||
| Date(s) of Event: | 5 Aug 2019 | |||||||||
| Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
