Synopsis
Builds a classification model for multiple classes based on a binary learner.
Description
A metaclassifier for handling multi-class datasets with 2-class classifiers. This class supports several strategies for multiclass classification including procedures which are capable of using error-correcting output codes for increased accuracy.
Input
- training set: expects: ExampleSet
Output
- model:
- example set:
Parameters
- classification strategies: What strategy should be used for multi class classifications?
- random code multiplicator: A multiplicator regulating the codeword length in random code modus.
- use local random seed: Indicates if a local random seed should be used.
- local random seed: Specifies the local random seed