Public Archive Task

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


  • Summary: Learn simultaneously two mult-class classification tasks. , the first is to classify documents from Yahoo! web directory and the second is to classifiy documents from DMOZ web directory. Labels are different amog taks but the tasks are related
    License: CC-BY-SA 3.0
    Tags: Classification DMOZ multi-class multi-task text web-pages Yahoo!
    Performance Measure: Accuracy
    Task Type: Multi Class Classification
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (10.7 KB) XML Matlab Octave

  • Summary: Classify real heart audio (also known as “beat classification”) into one of four(three) categories for Dataset A(B).
    License: CC-BY-SA 3.0
    Performance Measure: Accuracy
    Task Type: Multi Class Classification
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (9.8 KB) XML Matlab Octave

  • Summary: Locating each and every heart sound in the sound clips.
    License: CC-BY-SA 3.0
    Performance Measure: Accuracy
    Task Type: Multi Class Classification
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (10.6 KB) XML Matlab Octave

  • Summary: Collaborative filtering task for jokes
    License: CC-BY-SA 3.0
    Performance Measure: Accuracy
    Task Type: Regression
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (82.4 KB) XML Matlab Octave
    Files are converted on demand and the process can take up to a minute. Please wait until download begins.

  • Summary: Ratings prediction basing on other users' votes.
    License: CC-BY-SA 3.0
    Tags: collaborative-filtering Prediction recommender Regression sweetrs sweets
    Performance Measure: Mean Absolute Error
    Task Type: Regression
    Methods / Challenges: 1 methods, 0 challenges
    Download: HDF5 (28.2 KB) XML Matlab Octave

  • Summary: Predict if given patient has lung cancer basing on his genotype.
    License: CC-BY-SA 3.0
    Tags: cancer Classification genotype lung tumor
    Performance Measure: Accuracy
    Task Type: Binary Classification
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (66.5 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 goal of this experiment is to identify proteomic patterns in serum that distinguish ovarian cancer from non-cancer
    License: CC-BY-SA 3.0
    Tags: cancer Classification ovarian
    Performance Measure: Accuracy
    Task Type: Binary Classification
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (129.1 KB) XML Matlab Octave
    Files are converted on demand and the process can take up to a minute. Please wait until download begins.

  • Summary: Predict relapse basing on genotype. Gene expression data on tumor specimens from a total of 39 NSCLC samples
    License: CC-BY-SA 3.0
    Tags: cancer lung ontarion relapse
    Performance Measure: Accuracy
    Task Type: Binary Classification
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (33.3 KB) XML Matlab Octave
    Files are converted on demand and the process can take up to a minute. Please wait until download begins.

  • Summary: Classification of colon tumor basing on genotype
    License: CC-BY-SA 3.0
    Tags: clasification colon genotype tumor
    Performance Measure: Accuracy
    Task Type: Binary Classification
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (26.4 KB) XML Matlab Octave

  • Summary: Classification of patients of central nervous system embryonal tumor basing on gene expression.
    License: CC-BY-SA 3.0
    Tags: central expression gene nervous
    Performance Measure: Accuracy
    Task Type: Binary Classification
    Methods / Challenges: 0 methods, 0 challenges
    Download: HDF5 (66.5 KB) 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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