org.debellor.base.evaluator
Class TrainAndTest

java.lang.Object
  org.debellor.core.Cell
      org.debellor.base.evaluator.EvaluatorCell
          org.debellor.base.evaluator.TrainAndTest

public class TrainAndTest
extends EvaluatorCell

Implements evaluation of a cell (decision system) with Train+Test procedure. Samples are randomly shuffled before splitting into train and test sets. See EvaluatorCell for more information about usage. The evaluated cell must be erasable (it must correctly override Cell.onErase()).

Parameters:

• trainPercent: percentage of all samples to be used as training set. Should be between 1 and 100. Default: 70.
• repetitions: number of independent repetitions of the train+test procedure. Repetitions are independent and data are split randomly in each of them. Final results are summed over all repetitions (the same Score instance is used for all of them). Default: 1.
• score: name of the Score class to be used to measure quality of the evaluated decision system. See docs for EvaluatorCell.

Author:

Marcin Wojnarski

Nested Class Summary

Nested classes/interfaces inherited from class org.debellor.core.Cell

Cell.CellMethod, Cell.State, Cell.Stream

Field Summary

protected Cell.Stream

input

Fields inherited from class org.debellor.base.evaluator.EvaluatorCell

learner, score, scoreFromUser

Fields inherited from class org.debellor.core.Cell

parameters, random

Constructor Summary

TrainAndTest()

TrainAndTest(Cell cell)

Method Summary

protected void	onLearn() Learning procedure of the cell.
protected void	releaseData()

Methods inherited from class org.debellor.base.evaluator.EvaluatorCell

initScore, onErase, report, result, setInner, setScore

Methods inherited from class org.debellor.core.Cell

close, erase, getAvailableParams, getParameters, learn, newThread, newThread, next, onClose, onNext, onOpen, open, openInputStream, set, set, set, set, setAvailableParams, setParameters, setRandomSeed, setSource, state, toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

input

protected Cell.Stream input

Constructor Detail

TrainAndTest

public TrainAndTest()

TrainAndTest

public TrainAndTest(Cell cell)

Method Detail

onLearn

protected void onLearn()
                throws java.lang.Exception

Description copied from class: Cell

Learning procedure of the cell. For example, may train the internal decision model; read and buffer input data; calculate an evaluation measure of another cell; calculate data-driven parameters of a preprocessing algorithm (e.g. attribute means for normalization algorithm) etc. Called by Cell.learn().

Must be overridden in all subclasses that implement trainable cells. If your cell is not trainable, you must provide this information to the Cell base class by calling Cell.Cell(boolean) instead of Cell.Cell() in your constructor. Overriders may safely assume that the cell is in Cell.State.EMPTY state when onLearn is called - this is guaranteed by implementation of learn().

Overrides:

onLearn in class Cell

Throws:

java.lang.Exception

releaseData

protected void releaseData()

Overrides:

releaseData in class EvaluatorCell