Difference between revisions of "Clowdflows.unistra.fr"
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==What is ClowdFlows?== | ==What is ClowdFlows?== | ||
− | It is an online data science service: it enables the user to design and run data analysis workflows on a web browser, without installing any software. It provides lots of widgets from known libraries, e.g. Orange, SciKit, Weka. It can also call external web services. | + | It is an online data science service: it enables the user to design and run data analysis workflows on a web browser, without installing any software. It provides lots of widgets from known libraries, e.g. Orange, SciKit, Weka. It can also call external web services. Processing is performed on our servers and can access data remotely from files or databases. |
WorkFlows can be made public in order to include the URL in a publication to enable people to reproduce the experiments, and more generally to be used as tutorials. Examples are provided below. | WorkFlows can be made public in order to include the URL in a publication to enable people to reproduce the experiments, and more generally to be used as tutorials. Examples are provided below. |
Revision as of 15:50, 14 January 2016
ClowdFlows.unistra.fr is the node of the ClowdFlows.org network in the university of Strasbourg.
What is ClowdFlows?
It is an online data science service: it enables the user to design and run data analysis workflows on a web browser, without installing any software. It provides lots of widgets from known libraries, e.g. Orange, SciKit, Weka. It can also call external web services. Processing is performed on our servers and can access data remotely from files or databases.
WorkFlows can be made public in order to include the URL in a publication to enable people to reproduce the experiments, and more generally to be used as tutorials. Examples are provided below.
It is an open-source software. It can easily be extended. Our contributions are listed below.
Our contributions
In the relational data mining package
- the rule discovery tool, Tertius. See the example: Tertius from files on the family example
- the first-order Bayesian classifiers 1BC and 1BC2. See the example: 1BC on mutagenesis using cross-validation from DBMS
- Propositionalisation using Relaggs, cardinalisation and quantiles. See the example: Compare propositionalisation and J48 on urban blocks