Class GridSearchParameterLearner<S extends Observation,T extends Category>

Type Parameters:
S - the type of observations.
T - the type of categories.
All Implemented Interfaces:

public class GridSearchParameterLearner<S extends Observation,T extends Category> extends ParameterTrainer<S,T>
A grid-search approach for learning parameters. For each parameter with I=[l,u] being the boundaries for the parameter value of a given trainer, I is divided into partitions number of partitions. For each partition of each parameter the border points are chosen and a new classifier is learned with given parameter combination. From all combinations the combination where the classifier performs best is chosen. If depth > 1, the process is iterated: after selecting the best interval combination of the parameters, these intervals are again divided and the process is repeated depth many times.
Matthias Thimm
  • Constructor Details

    • GridSearchParameterLearner

      public GridSearchParameterLearner(Trainer<S,T> trainer, ClassificationTester<S,T> tester, int depth, int partitions)
      Creates a new grid-search parameter learner with the given arguments.
      trainer - some trainer.
      tester - some classification tester for measuring performance.
      depth - the depth of the recursion.
      partitions - the number of partitions.
  • Method Details