MeanErrorEvaluation

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nz.ac.waikato.mcennis.rat.graph.algorithm.evaluation
Class MeanErrorEvaluation

java.lang.Object
  nz.ac.waikato.mcennis.rat.graph.model.ModelShell
      nz.ac.waikato.mcennis.rat.graph.algorithm.evaluation.MeanErrorEvaluation

All Implemented Interfaces:: java.io.Serializable, Component, Algorithm, Model

public class MeanErrorEvaluation
extends ModelShell
implements Algorithm
extends ModelShell
implements Algorithm

Utilizes Given(user->artist) as ground truth and Derived(user->artist) as predicted values. Error is calculated from difference between derived and given link strengths. Derived links with no given are compared against link strength of 0 while the reverse are ignored. Herlocker, J., J. Konstan, L. Terveen, J. Reidl. 2004. Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems 22(1):5-53

See Also:: Serialized Form

Field Summary

Fields inherited from class nz.ac.waikato.mcennis.rat.graph.model.ModelShell
`listener`

Constructor Summary
`MeanErrorEvaluation()` Creates a new instance of Evaluation

Method Summary
`void`	`execute(Graph g)` Calculate all the evaluation metrics against the given graph.
`InputDescriptor[]`	`getInputType()` The input type describes all the different kinds of graph objects that are utilized (and hence required) by this object.
`OutputDescriptor[]`	`getOutputType()` The output type describes all the different kinds of graph objects that are created during the execution of this algorithm.
`Parameter[]`	`getParameter()` List of all parameters this component accepts.
`Parameter`	`getParameter(java.lang.String param)` Returns the specific parameter identified by its key-name.
`SettableParameter[]`	`getSettableParameter()` Returns settable (i.e.
`SettableParameter`	`getSettableParameter(java.lang.String param)` Return the settable parameter namede by this key-name.
`void`	`init(java.util.Properties map)` Parameters to be initialized 'name' - name of this instance of this algorithm.
`protected void`	`meanError(Graph g)`
`protected void`	`meanSquaredError(Graph g)`
`protected void`	`rootMeanSquaredError(Graph g)`
`protected void`	`scaleRecommendations(Graph g)`

Methods inherited from class nz.ac.waikato.mcennis.rat.graph.model.ModelShell
`addListener, fireChange`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Methods inherited from interface nz.ac.waikato.mcennis.rat.graph.model.Model
`addListener`

Constructor Detail

MeanErrorEvaluation

public MeanErrorEvaluation()

Creates a new instance of Evaluation

Method Detail

execute

public void execute(Graph g)

Calculate all the evaluation metrics against the given graph. TODO: add F-measure stastic

Specified by:: execute in interface Algorithm

Parameters:: g - graph to be modified

scaleRecommendations

protected void scaleRecommendations(Graph g)

meanError

protected void meanError(Graph g)

meanSquaredError

protected void meanSquaredError(Graph g)