Public Archive Task

Showing Items 1-10 of 30 on page 1 of 3: 1 2 3 Next


  • Summary: The diabetes task from the IDA Benchmark repository.
    License: CC-BY-SA 3.0
    Tags: Classification diabetes IDA_Benchmark_Repository
    Performance Measure: Accuracy
    Task Type: Binary Classification
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (389.1 KB) XML Matlab Octave
    Files are converted on demand and the process can take up to a minute. Please wait until download begins.

  • Summary: Simple demo classification task on the banana dataset
    License: CC-BY-SA 3.0
    Tags: banana Classification demo
    Performance Measure: Accuracy
    Task Type: Binary Classification
    Methods / Challenges: 1 methods, 0 challenges
    Download: HDF5 (52.8 KB) XML Matlab Octave
    Files are converted on demand and the process can take up to a minute. Please wait until download begins.

  • Summary: A simple regression task on the Abalone data
    License: CC-BY-SA 3.0
    Tags: abalone Regression
    Performance Measure: Root Mean Squared Error
    Task Type: Regression
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (50.8 KB) XML Matlab Octave
    Files are converted on demand and the process can take up to a minute. Please wait until download begins.

  • Summary: The standard task for the pima indian diabetes binary classification dataset
    License: CC-BY-SA 3.0
    Tags: binary Classification diabetes pima
    Performance Measure: Accuracy
    Task Type: Binary Classification
    Methods / Challenges: 1 methods, 1 challenges
    Download: HDF5 (20.8 KB) XML Matlab Octave

  • Summary: The standard task for the pima indian diabetes binary classification dataset
    License: CC-BY-SA 3.0
    Tags: binary Classification diabetes pima roc
    Performance Measure: ROC Curve
    Task Type: Binary Classification
    Methods / Challenges: 1 methods, 0 challenges
    Download: HDF5 (20.8 KB) XML Matlab Octave

  • Summary: minimize the test error in six different scenarios
    License: CC-BY-SA 3.0
    Performance Measure: Accuracy
    Task Type: Binary Classification
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (110.5 KB) XML Matlab Octave
    Files are converted on demand and the process can take up to a minute. Please wait until download begins.

  • Summary: The standard task for the iris dataset
    License: CC-BY-SA 3.0
    Tags: demo multiclass
    Performance Measure: Accuracy
    Task Type: Multi Class Classification
    Methods / Challenges: 2 methods, 1 challenges
    Download: HDF5 (12.9 KB) XML Matlab Octave

  • Summary: The standard task for the boston housing dataset
    License: CC-BY-SA 3.0
    Tags: boston housing Regression scaled uci
    Performance Measure: Root Mean Squared Error
    Task Type: Regression
    Methods / Challenges: 1 methods, 0 challenges
    Download: HDF5 (16.4 KB) XML Matlab Octave

  • Summary: The standard task for the boston housing dataset
    License: CC-BY-SA 3.0
    Tags: boston housing Regression uci
    Performance Measure: Root Mean Squared Error
    Task Type: Regression
    Methods / Challenges: 1 methods, 0 challenges
    Download: HDF5 (16.4 KB) XML Matlab Octave

  • Summary: The banana task from the IDA Benchmark repository.
    License: CC-BY-SA 3.0
    Tags: Classification IDA_Benchmark_Repository
    Performance Measure: Accuracy
    Task Type: Binary Classification
    Methods / Challenges: 1 methods, 0 challenges
    Download: HDF5 (2.5 MB) XML Matlab Octave
    Files are converted on demand and the process can take up to a minute. Please wait until download begins.

Showing Items 1-10 of 30 on page 1 of 3: 1 2 3 Next


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.

Data | Task | Method | Challenge

Acknowledgements

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