com.emphysic.myriad.core.data.roi

Interface MLROIFinder

All Superinterfaces:

com.esotericsoftware.kryo.KryoSerializable, ObjectMap, ROIFinder

All Known Implementing Classes:

AdaptiveSGDROIFinder, GradMachineROIFinder, MLROIConfFinder, PassiveAggressiveROIFinder, SGDROIFinder, SVMROIFinder

public interface MLROIFinder
extends ROIFinder

MLROIFinder - ROIFinder based on machine learning techniques.

Method Summary

Modifier and Type	Method and Description
double	negativeClass() The numeric label assigned to negative samples i.e.
double	positiveClass() The numeric label assigned to positive samples i.e.
double	predict(Dataset data) Returns the predicted class/value of the sample
double	predict(double[] data) Returns the predicted class/value of the sample
void	train(double[][] X, int[] y) Trains the Region Of Interest finder on new data

Methods inherited from interface com.emphysic.myriad.core.data.roi.ROIFinder

fromFile, isROI, isROI

Methods inherited from interface com.emphysic.myriad.core.data.util.ObjectMap

getObjectMap, getSerializationVersion, getVersion, init, initCurrentVersion, initPreviousVersion, initUnknownVersion, load, read, save, write

Method Detail

train

void train(double[][] X,
           int[] y)
    throws java.lang.Exception

Trains the Region Of Interest finder on new data

Parameters:

X - N examples with M features per example

y - N labels for the N examples in X

Throws:

java.lang.Exception - if an error occurs

predict

double predict(double[] data)
        throws java.lang.Exception

Returns the predicted class/value of the sample

Parameters:

data - sample to predict

Returns:

predicted label / value

Throws:

java.lang.Exception - if an error occurs

predict

double predict(Dataset data)
        throws java.lang.Exception

Returns the predicted class/value of the sample

Parameters:

data - sample to predict

Returns:

predicted label / value

Throws:

java.lang.Exception - if an error occurs

positiveClass

double positiveClass()

The numeric label assigned to positive samples i.e. samples that contain ROI

Returns:

the value assigned to positive samples

negativeClass

double negativeClass()

The numeric label assigned to negative samples i.e. samples that do not contain ROI

Returns:

the value assigned to negative samples