pharmine

Scale the training set

1. Put File Reader node (IO->Read) to workbench and configure it to load a training set from a file.
2. Put Normalizer node (Data Manipulation->Column) to workbench and connect the output port from the File Reader node to its input port.
• Configure it by choosing Min-Max Normalization with the Min set as 0.0 and Max set as 1.0.
• Select the columns to normalize.
3. Put Model Writer node (IO->Write) to workbench and connect the model port of the Normalizer node to its input port. Configure it to save the model to a file.
4. Execute all nodes.

Scale the testing set

1. Put File Reader node (IO->Read) to workbench and configure it to load a testing set from a file.
2. Put Normalizer (Apply) node (Data Manipulation->Column) to workbench and connect the output port from the File Reader node to its input port.
3. Put Model Reader node (IO->Read) to workbench and connect its output port to the model port of the Normalizer (Apply) node. Configure it to load the model that is saved during the scaling of the training set.
4. Execute all nodes.

KNIME score full marks for its ease in scaling descriptors.

This entry was posted by Yap Chun Wei on Wednesday, March 19th, 2008 at 10:09 pm and is filed under Data mining, Review. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.