Class | Description |
---|---|
C45 |
Class to implement the C4.5 algorithm
|
ClassificationFilter |
The Classification Filter begins with n equal-sized disjoint subsets of the training set E (done with n-fold cross validation)
and the empty output set A of detected noisy examples.
|
KNN |
The KNN algorithm tries to find the K nearest instances in the
training data, selecting the most present class.
|
Main |
Main class of the algorithm
|
Parameters |
Main class to parse the parameters of the algorithm
|
PartitionScheme |
This class implements a stratified scheme (equal number of examples of each class in each partition) to partition a dataset
|