NG Learner (beta)

This node learns a classification model based on Neighborgrams. The model will cover all classes, for which Neighborgrams are constructed (as specified in the dialog). For details on the construction and individual dialog parameters, refer to the description of the NG Construct&View node. The few additional parameters are briefly commented on below:


The purity value for the Neighborgram cluster candidates. The value must be in a range 0, 1 (though any value less than 0.6 is in most cases unreasonable). A higher value will cause more clusters to be identified.
Minimum coverage of a cluster
This parameter defines the termination criterion, i.e. the minimum of the accumulated coverage of each clusters. If the best next clusters covers less than this value, the clustering stops.

Input Ports

Training data.

Output Ports

Clustering statistics showing how many clusters were found in which universe (if any).
Classification model.


Cluster Statistics
Shows simple cluster statistics (counts).


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