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We built this web site as a repository for your machine learning data.
Upload your data, find interesting data sets, exchange solutions, compare yourself against other methods.

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Choose between

  • A raw data set.
  • A learning task defined on existing data sets.
  • Describing a machine learning method.
  • Creating a challenge by grouping existing tasks.

Recent Items

  • Data test data 2014-07-02 16:10
    test data
  • Data worldwide-companies-r10k 2013-11-18 15:15
    random sample from business information database
  • Data golfdata 2013-10-23 22:01
    Results of
  • Data CHEMDNER-training 2013-08-01 17:29
    CHEMDNER training set: Chemical compound and drug name recognition task
  • Data Wearable Accelerometers Activity 2013-07-30 04:38
    A dataset with 5 classes (sitting-down, standing-up, standing, walking, and sitting) collected on 8 hours of activities of 4 healthy subjects.

How does it work?

This repository manages the following types of objects.
  • Data Sets - Raw data as a collection of similarily structured objects.
  • Material and Methods - Descriptions of the computational pipeline.
  • Learning Tasks - Learning tasks defined on raw data.
  • Challenges - Collections of tasks which have a particular theme.
Between data sets and tasks, the relationship is one-to-many, as a data set can give rise to many different learning tasks. A method can also be applied to several different tasks, giving rise to solutions. On the other hand, a task can have many solutions, but each solution belongs to a certain learning task. These relationships are illustrated in the image.

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