UCI Machine Learning Repository

Dataset Identification:

Resource Abstract:
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.
Citation
Title UCI Machine Learning Repository
publication  Date   2007
Keywords:
Theme keywords (theme):
11103 Communication Science
40904 Artificial Intelligence, Image and Language Processing
409 Computer Science
111 Social Sciences
12 Social and Behavioural Sciences
1 Humanities and Social Sciences
44 Computer Science, Electrical and System Engineering
4 Engineering Sciences
thesaurus name >
Title DFG
Location keywords:
algorithms - data processing
machine learning
computer science
Theme keywords (theme):
open
thesaurus name >
Title re3 Deposit
publication  Date   2015-01-01
Theme keywords (theme):
Machine Learning
Computer Science
thesaurus name >
Title Science Domain > Computer Science
publication  Date   2017-03-28
other Citation Details  Cinergi keyword enhanced.File generated at Tue Mar 28 20:02:18 UTC 2017
Theme keywords (theme):
Analysis
thesaurus name >
Title Method > Information Processing
publication  Date   2017-03-28
other Citation Details  Cinergi keyword enhanced.File generated at Tue Mar 28 20:02:18 UTC 2017
Theme keywords (theme):
Repository
thesaurus name >
Title Resource Type > Repository
publication  Date   2017-03-28
other Citation Details  Cinergi keyword enhanced.File generated at Tue Mar 28 20:02:18 UTC 2017
Theme keywords (theme):
National Science Foundation
University of California
School of Information and Computer Science
thesaurus name >
Title Virtual International Authority File (VIAF) Corporate Names
publication  Date   2017-03-28
other Citation Details  Cinergi keyword enhanced.File generated at Tue Mar 28 20:02:18 UTC 2017
Theme keywords (theme):
Data Set
thesaurus name >
Title Resource Type > Data Set
publication  Date   2017-03-28
other Citation Details  Cinergi keyword enhanced.File generated at Tue Mar 28 20:02:18 UTC 2017
Resource language:  true
Constraints on resource usage:
Constraints
Use limitation statement:
Disclaimer - While every effort has been made to ensure that these data are accurate and reliable within the limits of the current state of the art, NOAA cannot assume liability for any damages caused by any errors or omissions in the data, nor as a result of the failure of the data to function on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.
Constraints on resource usage:
Legal Constraints
Access Constraints  otherRestrictions
use constraint:  otherRestrictions
Other constraints
WMO Essential
Additional information on resource:
point of contact - custodian
organisation Name  Rexa.info
point of contact - custodian
organisation Name  National Science Foundation
point of contact - custodian
organisation Name  University of California, Irvine, School of Information and Computer Science, Center for Machine Learning and Intelligent Systems
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Resource distribution information

Format
Format name Resource URL
Format version 
Format
Format name API
Format version 
Digital Transfer Options
Linkage for online resource
name Repository URL
URL: http://archive.ics.uci.edu/ml/index.html
link function information
Digital Transfer Options
Linkage for online resource
name API
URL: 
link function download

Metadata data stamp:  
Metadata contact - pointOfContact
organisation Name  Earthcube CINERGI Metadata Pipeline
position Name CINERGI Metadata Contact
Contact information
Address
electronic Mail Address metadata@earthcube.org
Metadata scope code  service
Metadata language  en
standard version:  2003
Metadata record identifier:  r3d100010960
URI for dataset described: > http://archive.ics.uci.edu/ml/index.html

Metadata record format is ISO19139-2 XML (MI_Metadata)