View Friedman-datasets fri_c4_500_25 (public)
























- Summary
(No information yet)
- License
- unknown (from Weka repository)
- Dependencies
- Tags
- arff slurped Weka
- Attribute Types
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# Instances: 500 / # Attributes: 26
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- Original Data Format
- arff
- Name
- fri_c4_500_25
- Version mldata
- 0
- Comment
- Names
- oz1,oz2,oz3,oz4,oz5,oz6,oz7,oz8,oz9,oz10,
- Types
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- Data (first 10 data points)
oz1 oz2 oz3 oz4 oz5 oz6 oz7 oz8 oz9 oz10 ... -0.64... 0.20... 0.16... 1.01... -0.27... -0.01... -0.77... 0.55... -1.42... 0.53... ... -1.00... -1.63... -0.51... -0.19... -0.54... 0.32... 0.40... -0.16... -0.80... 0.31... ... 0.35... -0.09... 0.55... 1.33... 0.46... -0.15... -0.81... -1.65... 1.07... 1.47... ... 0.76... 1.02... -0.63... -0.96... -0.37... -0.67... -1.24... 0.31... -0.99... -0.57... ... 1.09... 0.98... 2.14... 1.63... 2.49... 0.58... 1.60... -1.13... 1.53... 0.52... ... 0.17... -0.29... -0.28... -0.33... -0.27... -1.11... -1.75... -1.55... -0.44... 0.99... ... -0.89... -0.36... -0.76... -1.45... -1.09... -0.93... 1.24... -1.23... 1.76... -1.69... ... -0.52... -0.50... -0.01... 1.39... -0.29... 1.91... 1.33... 0.85... 0.32... 0.06... ... 1.19... 0.64... 0.53... 0.01... 0.90... -0.04... 0.40... -0.84... -0.51... -0.11... ... 2.30... 1.76... 1.73... 0.84... 3.05... -1.07... -0.94... -1.33... -0.15... 0.53... ... ... ... ... ... ... ... ... ... ... ... ...
- Description
A zip file containing 80 artificial datasets generated from the Friedman function donated by Dr. M. Fatih Amasyali (Yildiz Technical Unversity) (Friedman-datasets.zip, 5,802,204 Bytes)
- URLs
- (No information yet)
- Publications
- Data Source
- http://www.ce.yildiz.edu.tr/en/myindex.php?id=14 http://www.ce.yildiz.edu.tr/
- Measurement Details
- Usage Scenario
- revision 1
- by mldata on 2010-11-06 10:01
- revision 2
- by jaakkopeltonen on 2010-11-22 18:26
- revision 3
- by jaakkopeltonen on 2010-11-22 18:26
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Acknowledgements
This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
http://www.pascal-network.org/.