org.ai_heuristic.algo

Class AlgorithmCompareTree

java.lang.Object

org.ai_heuristic.functs.Function

org.ai_heuristic.algo.AlgorithmCompare

org.ai_heuristic.algo.AlgorithmCompareTree

All Implemented Interfaces:

FunctionDef

Direct Known Subclasses:

NearestNeighbour

public abstract class AlgorithmCompareTree
extends AlgorithmCompare

Base class for algorithms that perform a direct comparison between own (dataset) dataset and a set of input datasets. Note that own dataset is static and not changed or realised through a learning phase. It would typically be added as part of the initialisation process, or along with a group of input datasets to compare with each other.

Author:

Kieran Greer

Field Summary

Fields

Modifier and Type	Field and Description
protected int	bs The bucket size for the tree
protected KD_Tree	kdTree The tree that stores the balanced datasets

Fields inherited from class org.ai_heuristic.algo.AlgorithmCompare

bestEval, evalMetric

Fields inherited from class org.ai_heuristic.functs.Function

config, mathCompare, valueType

Constructor Summary

Constructors

Constructor and Description
AlgorithmCompareTree() Create a new instance of AlgorithmCompareTree.
AlgorithmCompareTree(java.lang.String thisValueType) Create a new instance of AlgorithmCompareTree.
AlgorithmCompareTree(java.lang.String thisValueType, java.util.HashMap<java.lang.String,?> thisConfig) Create a new instance of AlgorithmCompareTree.
AlgorithmCompareTree(java.lang.String thisValueType, java.util.HashMap<java.lang.String,?> thisConfig, FunctionMetric thisEvalMetric, EvaluateMathDef mathEval) Create a new empty instance of AlgorithmCompareTree.

Method Summary

Modifier and Type	Method and Description
KD_Tree	getDatasetTree() Get the datasets/points that are this algorithm's tree.
protected void	initialise() Initialise the function values, setting the config parameters or other.
void	resetValues() Reset the evaluation results for a new test scenario.
void	setDatasetTree(KD_Tree theDatasets) Set the datasets/points that are this algorithm's tree.
protected java.util.LinkedHashMap<java.lang.String,MetricValue>	updateTree(MetricDataset dataset) Update the kd-tree by adding any new dataset points, as determined by the value name.

Methods inherited from class org.ai_heuristic.algo.AlgorithmCompare

getBestEvaluation

Methods inherited from class org.ai_heuristic.functs.Function

checkValueType, createFunction, createFunction, createFunction, evaluate, getConfigParams, 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

bs

protected int bs

The bucket size for the tree

kdTree

protected KD_Tree kdTree

The tree that stores the balanced datasets

Constructor Detail

AlgorithmCompareTree

public AlgorithmCompareTree()
                     throws java.lang.Exception

Create a new instance of AlgorithmCompareTree.

Throws:

java.lang.Exception - any error.

AlgorithmCompareTree

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

Create a new instance of AlgorithmCompareTree.

Parameters:

thisValueType - the type of object being evaluated.

Throws:

java.lang.Exception - any error.

AlgorithmCompareTree

public AlgorithmCompareTree(java.lang.String thisValueType,
                            java.util.HashMap<java.lang.String,?> thisConfig)
                     throws java.lang.Exception

Create a new instance of AlgorithmCompareTree.

Parameters:

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

thisConfig - list of initialisation function-specific parameters.

Throws:

java.lang.Exception - any error.

AlgorithmCompareTree

public AlgorithmCompareTree(java.lang.String thisValueType,
                            java.util.HashMap<java.lang.String,?> thisConfig,
                            FunctionMetric thisEvalMetric,
                            EvaluateMathDef mathEval)
                     throws java.lang.Exception

Create a new empty instance of AlgorithmCompareTree.

Parameters:

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

thisConfig - list of initialisation function-specific parameters.

thisEvalMetric - the distance function.

mathEval - for simple math comparisons.

Throws:

java.lang.Exception - any error.

Method Detail

initialise

protected void initialise()
                   throws java.lang.Exception

Initialise the function values, setting the config parameters or other.

Overrides:

initialise in class AlgorithmCompare

Throws:

java.lang.Exception - any error.

resetValues

public void resetValues()

Reset the evaluation results for a new test scenario.

Overrides:

resetValues in class AlgorithmCompare

updateTree

protected java.util.LinkedHashMap<java.lang.String,MetricValue> updateTree(MetricDataset dataset)
                                                                    throws java.lang.Exception

Update the kd-tree by adding any new dataset points, as determined by the value name.

Parameters:

dataset - list of dataset points, of type MetricValue.

Returns:

re-formatted dataset as hashtable of name-value pairs.

Throws:

java.lang.Exception - any error.

setDatasetTree

public void setDatasetTree(KD_Tree theDatasets)

Set the datasets/points that are this algorithm's tree.

Parameters:

theDatasets - the datasets/points to compare with. Of type MetricValue.

getDatasetTree

public KD_Tree getDatasetTree()

Get the datasets/points that are this algorithm's tree.

Returns:

the value of kdTree.