CostSensitiveClassifier (3.6)

Learner

A metaclassifier that makes its base classifier cost-sensitive. Two methods can be used to introduce cost-sensitivity: reweighting training instances according to the total cost assigned to each class; or predicting the class with minimum expected misclassification cost (rather than the most likely class). Performance can often be improved by using a Bagged classifier to improve the probability estimates of the base classifier.

(based on WEKA 3.6)

For further options, click the 'More' - button in the dialog.

All weka dialogs have a panel where you can specify classifier-specific parameters.

Input Ports

  1. Type: Data
    Training data

Output Ports

  1. Type: Weka 3.6 Classifier
    Trained classifier

Extension

This node is part of the extension

KNIME Weka Data Mining Integration (3.6)

v2.10.2

Short Link

Drag node into KNIME Analytics Platform