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Welcome

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

Challenge UCI example challenge 2011-10-25 16:11
Challenge showing mldata.org features
Data Ratings of sweets 2011-10-23 00:58
Ratings of sweets for collaborative-filtering. Data gathered on http://sweetrs.org/ website.
Task Jokes ratings prediction 2011-09-29 12:18
Collaborative filtering task for jokes
Method simple-test-method 2011-09-29 10:28
Task Sweets recommender system 2011-09-27 11:18
Ratings prediction basing on other users' votes.

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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