probabilityCalibrationTrees · Provides probability calibration trees (PCTs) for local calibration of class probability estimates. To achieve calibration of a base learner, the PCT class must be used as the meta learner in the CascadeGeneralization class, which is also included in this package. The classifier to be calibrated must be used as the base learner in the CascadeGeneralization class. The CascadeGeneralization class can also be used independently to perform CascadeGeneralization for ensemble learning. The code for PCTs is largely the same as the LMT code for growing logistic model trees. For more details, see the ACML paper on probability calibration trees.

Table Of Contents

• Latest Version
• All Versions
• View Java Class Source Code in JAR file

Latest Version

Download nz.ac.waikato.cms.weka : probabilityCalibrationTrees JAR file - Latest Versions:

• Latest Stable: 1.0.0.jar

All Versions

Download nz.ac.waikato.cms.weka : probabilityCalibrationTrees JAR file - All Versions:

Version		Vulnerabilities	Size	Updated
1.0.x	probabilityCalibrationTrees-1.0.0.jar		35.45 KB	Nov 26, 2017

View Java Class Source Code in JAR file

1. Download JD-GUI to open JAR file and explore Java source code file (.class .java)
2. Click menu "File → Open File..." or just drag-and-drop the JAR file in the JD-GUI window probabilityCalibrationTrees-1.0.0.jar file.
   Once you open a JAR file, all the java classes in the JAR file will be displayed.

weka.classifiers.meta

├─ weka.classifiers.meta.CascadeGeneralization.class - [JAR]

weka.classifiers.trees.lmt

├─ weka.classifiers.trees.lmt.ComparePCTNode.class - [JAR]

├─ weka.classifiers.trees.lmt.PCTNode.class - [JAR]

├─ weka.classifiers.trees.lmt.PCTNodeBase.class - [JAR]

weka.classifiers.trees

├─ weka.classifiers.trees.PCT.class - [JAR]