Public Archive Data

Showing Items 41-50 of 873 on page 5 of 88: Previous 1 2 3 4 5 6 7 8 9 10 Next Last


  • Summary: Artificial data generated from the Friedman function, part of a collection of 80 data sets. This particular set has 50 features, 1 output (51st feature), colinearity degree 1, and 1000 instances.
    Data Shape: 51 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 (409.0 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: 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 2, and 250 instances.
    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: Artificial data generated from the Friedman function, part of a collection of 80 data sets. This particular set has 5 features, 1 output (6th feature), colinearity degree 2, and 500 instances.
    Data Shape: 6 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 (34.0 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: Artificial data generated from the Friedman function, part of a collection of 80 data sets. This particular set has 25 features, 1 output (26th feature), colinearity degree 4, and 500 instances.
    Data Shape: 26 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 (112.1 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 50 features, 1 output (51st feature), colinearity degree 2, and 1000 instances.
    Data Shape: 51 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 (409.0 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: 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 4, and 250 instances.
    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: Artificial data generated from the Friedman function, part of a collection of 80 data sets. This particular set has 25 features, 1 output (26th feature), colinearity degree 2, and 500 instances.
    Data Shape: 26 attributes, 500 instances (Floating Point)
    License: unknown (from Weka repository)
    Tags: arff colinearity Friedman-function slurped Weka
    Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
    Download: HDF5 (112.1 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 5 features, 1 output (6th feature), colinearity degree 0, and 1000 instances.
    Data Shape: 6 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 (57.4 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: Artificial data generated from the Friedman function, part of a collection of 80 data sets. This particular set has 5 features, 1 output (6th feature), colinearity degree 1, and 100 instances.
    Data Shape: 6 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 (15.2 KB) XML CSV ARFF LibSVM Matlab Octave

  • Summary: Artificial data generated from the Friedman function, part of a collection of 80 data sets. This particular set has 5 features, 1 output (6th feature), colinearity degree 3, and 500 instances.
    Data Shape: 6 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 (34.0 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.

Showing Items 41-50 of 873 on page 5 of 88: Previous 1 2 3 4 5 6 7 8 9 10 Next Last


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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.

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Acknowledgements

This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
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