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Presentation - The Evolution of e-Research: Machines...

Created: 2010-10-28 07:09:43 | Last updated: 2010-10-29 01:20:15

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Blastn-ClustalW (1)

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Created: 2010-10-27 | Last updated: 2010-10-27

Credits: Kalpana

Polygon buffer - Using pyWPS (1)

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Basic example on how to integrate a Web Processing Service (WPS) using  PyWPS's WSDL/SOAP The workflow will accept a GML file with featureCollection where polyon is described using gml:coordinate element structure. This GMl is easely generated with GDAL. The coodinate structure will be converted to WKT and used to create a polygon using shapely, the output will be a buffer polygon with a defined width. Output polygon will replace the orginal polygon and the existing XML will be return...

Created: 2010-10-26 | Last updated: 2010-10-26

Credits: Jorgejesus

Concatenate Examples (1)

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This process I'm using for preprocessing is concatenating the values of att2 for all the same values of att1 in att3. ps: Thanks to Matthias for his help.

Created: 2010-10-26 | Last updated: 2010-10-26

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Presentation - Collaboration and Sharing of Computat...

Created: 2010-10-21 20:16:46 | Last updated: 2010-10-21 20:19:25

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Training Data DAT

Created: 2010-10-21 18:15:51 | Last updated: 2010-10-21 18:15:52

Credits: Rapido

License: Creative Commons Attribution-Share Alike 3.0 Unported License

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Training Data AML

Created: 2010-10-21 18:11:43

Credits: Rapido

License: Creative Commons Attribution-Share Alike 3.0 Unported License

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Compare SVM, Linear Regression, Linear Discriminant ...

Created: 2010-10-21 16:56:37 | Last updated: 2010-10-21 18:20:19

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X-Validation with One-Class SVM (1)

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With this example process, I intend to show how one might validate predictions done with a one class classifier. RapidMiner includes the One-Class SVM (part of libsvm) as introduced by Schoelkopf. I'm very interested in feedback concerning problems with or errors in this experiment. Note that the data set (Sonar) is just a toy data set chosen for demonstration - learning a one class classifier on it won't give you any good results! DESCRIPTION The basic idea is to partition the data set...

Created: 2010-10-20 | Last updated: 2010-10-20

Find best feature selection method. (1)

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This processes searches for the best method for feature selection and the best feature subset size. Inside a parameter loop the number of selected features and the feature selection methods are evaluated with a 10fold cross-validation. The Feature Selection Extension ( https://sourceforge.net/projects/rm-featselext ) is required. BUGFIX: Please note that the plugin downloaded before 5th November contains a bug. Due to a bug in RM the TopK-operator sorted the features in the wrong direction. ...

Created: 2010-10-19 | Last updated: 2010-12-10