Public Archive Data
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uci-20070111 breast-w - submitted by mldata 2548 views, 4402 downloads, 0 comments
last edited by mldata - Sep 14, 2011, 15:57 CET Rating
- Summary:
(No information yet)
- Data Shape: 10 attributes, 699 instances (Integer,String)
- License: unknown (from Weka repository)
- Tags: arff slurped Weka
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (74.3 KB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
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uci-20070111 primary-tumor - submitted by mldata 2773 views, 4381 downloads, 0 comments
last edited by mldata - Sep 14, 2011, 15:57 CET Rating
- Summary:
(No information yet)
- Data Shape: 18 attributes, 339 instances (String)
- License: unknown (from Weka repository)
- Tags: arff slurped Weka
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (262.5 KB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
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uci-20070111 spectf_train - submitted by mldata 2505 views, 5138 downloads, 0 comments
last edited by mldata - Sep 14, 2011, 15:57 CET Rating
- Summary:
(No information yet)
- Data Shape: 45 attributes, 80 instances (Integer)
- License: unknown (from Weka repository)
- Tags: arff slurped Weka
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (29.4 KB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
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uci-20070111 kdd_coil_test-6 - submitted by mldata 2572 views, 3893 downloads, 0 comments
last edited by mldata - Sep 14, 2011, 15:57 CET Rating
- Summary:
(No information yet)
- Data Shape: 12 attributes, 133 instances (Floating Point,String)
- License: unknown (from Weka repository)
- Tags: arff slurped Weka
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (43.4 KB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
(No information yet)
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uci-20070111 soybean - submitted by mldata 3312 views, 4650 downloads, 0 comments
last edited by mldata - Sep 14, 2011, 15:57 CET Rating
- Summary:
(No information yet)
- Data Shape: 36 attributes, 683 instances (String)
- License: unknown (from Weka repository)
- Tags: arff slurped Weka
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (1.0 MB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
(No information yet)
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Friedman-datasets fri_c1_1000_10 - submitted by mldata 2529 views, 4737 downloads, 0 comments
last edited by mldata - Sep 14, 2011, 15:57 CET Rating
- Summary:
(No information yet)
- Data Shape: 11 attributes, 1000 instances (Floating Point)
- License: unknown (from Weka repository)
- Tags: arff slurped Weka
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (96.5 KB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
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Friedman-datasets fri_c0_250_10 - submitted by mldata 2158 views, 4673 downloads, 0 comments
last edited by mldata - Sep 14, 2011, 15:57 CET Rating
- Summary:
(No information yet)
- Data Shape: 11 attributes, 250 instances (Floating Point)
- License: unknown (from Weka repository)
- Tags: arff slurped Weka
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (32.0 KB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
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Friedman-datasets fri_c0_500_50 - submitted by mldata 2378 views, 5032 downloads, 0 comments
last edited by mldata - Sep 14, 2011, 15:57 CET Rating
- Summary:
(No information yet)
- Data Shape: 51 attributes, 500 instances (Floating Point)
- License: unknown (from Weka repository)
- Tags: arff slurped Weka
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (209.8 KB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
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Friedman-datasets fri_c0_100_50 - submitted by mldata 2129 views, 4726 downloads, 0 comments
last edited by mldata - Sep 14, 2011, 15:57 CET Rating
- Summary:
(No information yet)
- Data Shape: 51 attributes, 100 instances (Floating Point)
- License: unknown (from Weka repository)
- Tags: arff slurped Weka
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (50.4 KB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
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Friedman-datasets fri_c0_500_10 - submitted by mldata 4512 views, 5066 downloads, 0 comments
last edited by jaakkopeltonen - Sep 14, 2011, 15:57 CET Rating
- Summary:
Artificial data generated from the Friedman function, part of a collection of 80 data sets. This particular set has 10 features, 1 output (11th feature), colinearity degree 0, and 500 instances.
- Data Shape: 11 attributes, 500 instances (Floating Point)
- License: unknown (from Weka repository)
- Tags: arff slurped Weka
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (53.5 KB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
Artificial data generated from the Friedman function, part of a collection of 80 data sets. This particular set has 10 features, 1 output (11th feature), colinearity degree 0, and 500 instances.
Disclaimer
We are acting in good faith to make datasets submitted for the use of the scientific community available to everybody, but if you are a copyright holder and would like us to remove a dataset please inform us and we will do it as soon as possible.
Acknowledgements
This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
http://www.pascal-network.org/.