Package dk.alexandra.fresco.stat.mlp.evaluation

Class AccuracyBinary

Object

AccuracyBinary

All Implemented Interfaces:

Computation<SInt,ProtocolBuilderNumeric>

public class AccuracyBinary
extends Object
implements Computation<SInt,ProtocolBuilderNumeric>

Return the number of correct predictions in the given data set. It's assumed that there's only two different labels, 0 and 1. If there are more possibilities, use Accuracy instead.

Constructor Summary

Constructors

Constructor	Description
AccuracyBinary(MLP neuralNetwork, List<ArrayList<DRes<SFixed>>> data, ArrayList<DRes<SInt>> labels)

Method Summary

Modifier and Type	Method	Description
DRes<SInt>	buildComputation(ProtocolBuilderNumeric builder)

Methods inherited from class Object

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

Constructor Details

AccuracyBinary

public AccuracyBinary(MLP neuralNetwork, List<ArrayList<DRes<SFixed>>> data, ArrayList<DRes<SInt>> labels)

Method Details

buildComputation

public DRes<SInt> buildComputation(ProtocolBuilderNumeric builder)

Specified by:

buildComputation in interface Computation<SInt,ProtocolBuilderNumeric>