org.ai_heuristic.algo

Class AlgorithmLearn

java.lang.Object

org.ai_heuristic.functs.Function

org.ai_heuristic.algo.AlgorithmLearn

All Implemented Interfaces:

FunctionDef

Direct Known Subclasses:

Markov

public abstract class AlgorithmLearn
extends Function

Base class for algorithms that required a supervised or unsupervised learning phase, before being able to classify or categorise other datasets.

Author:

Kieran Greer

Field Summary

Fields

Modifier and Type	Field and Description
protected FunctionLearn	evalMetric The metric to calculate the distance with

Fields inherited from class org.ai_heuristic.functs.Function

config, mathCompare, valueType

Constructor Summary

Constructors

Constructor and Description
AlgorithmLearn() Create a new instance of AlgorithmLearn.
AlgorithmLearn(FunctionLearn thisEvalMetric) Create a new instance of AlgorithmLearn.
AlgorithmLearn(java.lang.String thisValueType) Create a new instance of AlgorithmLearn.
AlgorithmLearn(java.lang.String thisValueType, FunctionLearn thisEvalMetric) Create a new instance of AlgorithmLearn.

Method Summary

Modifier and Type	Method and Description
abstract ReplySet	train(MetricDataset dataset) Train the function based on the supervised training method, using the dataset as input.

Methods inherited from class org.ai_heuristic.functs.Function

checkValueType, createFunction, createFunction, createFunction, evaluate, getConfigParams, initialise, innerObject, isLegalNumber, setConfigParams, setEvaluator, setValueType

Methods inherited from class java.lang.Object

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

Field Detail

evalMetric

protected FunctionLearn evalMetric

The metric to calculate the distance with

Constructor Detail

AlgorithmLearn

public AlgorithmLearn()
               throws java.lang.Exception

Create a new instance of AlgorithmLearn. The valueType is set to null and the eval function is set to SimpleMathCompare.

Throws:

java.lang.Exception - any error.

AlgorithmLearn

public AlgorithmLearn(java.lang.String thisValueType)
               throws java.lang.Exception

Create a new instance of AlgorithmLearn.

Parameters:

thisValueType - the type of object being evaluated. Can be null if set later or not used.

Throws:

java.lang.Exception - any error.

AlgorithmLearn

public AlgorithmLearn(FunctionLearn thisEvalMetric)
               throws java.lang.Exception

Create a new instance of AlgorithmLearn.

Parameters:

thisEvalMetric - the distance function.

Throws:

java.lang.Exception - any error.

AlgorithmLearn

public AlgorithmLearn(java.lang.String thisValueType,
                      FunctionLearn thisEvalMetric)
               throws java.lang.Exception

Create a new instance of AlgorithmLearn.

Parameters:

thisValueType - the type of object being evaluated. Can be null if set later or not used.

thisEvalMetric - the distance function.

Throws:

java.lang.Exception - any error.

Method Detail

train

public abstract ReplySet train(MetricDataset dataset)
                        throws java.lang.Exception

Train the function based on the supervised training method, using the dataset as input.

Parameters:

dataset - the dataset, or any list of datasets, etc.

Returns:

the training result, wrapped in a ReplySet object, or null if one is not required. This can store any other object as its value and can be easily created using new ReplySet(obj).

Throws:

java.lang.Exception - any error.