Description:

C5.0 is the successor of the C4.5 decision tree algorithm/tool. In particular, it is faster and more memory-efficient.

C5.0 also supports boosting, variable misclassification costs, case weights, sampling, and cross-validation.

C5.0's attribute types are numbers, dates, times, timestamps, ordered discrete attributes, and nominal. Missing and NA values are supported.

Additional attributes can be defined by combinations of existing attributes.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download

Supported Operating Systems: Linux

Data Formats: Cfourpointfive

Tags: Classification, Decision Trees, Boosting, Decision Tree Learning, Rule Learning

Archive: download here

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