pharmine

1. Put File Reader node (IO->Read) to workbench and configure it to load a training set from a file.
2. Put Cross validation node (Meta) to workbench and connect the output port from the File Reader node to its input port.
• Configure it by setting Number of validations to 10.
• Ensure the Random sampling box is checked.
• Select the correct column for the Column with class labels listbox.
3. Open the Cross validation node Meta-workflow editor.
• Put K Nearest Neighbor node (Mining->Misc Classifiers) on the editor and connect the training data and test data output ports of the X-Partitioner node to the training data and test data input ports of the K Nearest Neighbor node, respectively.
• Configure it by setting the Number of neighbours to consider (k) to 3.
4. Exit the Meta-workflow editor and put Statistics View node (Statistics) to workbench and connect the error rates port from the Cross validation node to its input port.
5. Execute all nodes.

The above procedure shows how KNIME can be used to train and assess the performance of a model. However, it is not possible to automatically determine the optimum parameter value (e.g. Number of neighbours to consider (k) in the above procedure) for a machine learning/statistical method (According to their forum, this feature may be available in version 2.0). To determine the optimum parameter value, you have to do it manually by setting a parameter value, run all the nodes, record the mean error rates given in the Statistics View node, set another parameter value, run all the nodes again, record the mean error rates and so on, until you have evaluated all the parameter values that you are interested in. Then the parameter value which gives the lowest mean error rates will be the optimum parameter value of the machine learning/statistical method for the training set.

This entry was posted by Yap Chun Wei on Sunday, March 23rd, 2008 at 9:42 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.