marf.FeatureExtraction.RandomFeatureExtraction
Class RandomFeatureExtraction

java.lang.Object
  marf.Storage.StorageManager
      marf.FeatureExtraction.FeatureExtraction
          marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, IFeatureExtraction, IStorageManager

public class RandomFeatureExtraction
extends FeatureExtraction

Implementation of random feature extraction for testing as a baseline.

$Id: RandomFeatureExtraction.java,v 1.18 2007/12/18 03:45:42 mokhov Exp $

Since:

0.2.0

Version:

$Revision: 1.18 $

Author:

Serguei Mokhov

See Also:

Serialized Form

Field Summary

static int	DEFAULT_CHUNK_SIZE Default number (256) of doubles per chunk in a feature vector.
private static long	serialVersionUID For serialization versioning.

Fields inherited from class marf.FeatureExtraction.FeatureExtraction

adFeatures, oFeatureSet, oPreprocessing

Fields inherited from class marf.Storage.StorageManager

bDumpOnNotFound, iCurrentDumpMode, oObjectToSerialize, strFilename

Fields inherited from interface marf.FeatureExtraction.IFeatureExtraction

MARF_INTERFACE_CODE_REVISION

Fields inherited from interface marf.Storage.IStorageManager

DUMP_BINARY, DUMP_CSV_TEXT, DUMP_GZIP_BINARY, DUMP_HTML, DUMP_SQL, DUMP_XML, MARF_INTERFACE_CODE_REVISION, STORAGE_FILE_EXTENSIONS

Constructor Summary

RandomFeatureExtraction(IPreprocessing poPreprocessing)
RandomFeatureExtraction Constructor.

Method Summary

boolean	extractFeatures() Random Gaussian-based feature extraction.
boolean	extractFeatures(double[] padSampleData) Extracts features from the provided sample array.
protected boolean	extractFeaturesImplementation(Sample poSample) Does the actual business logic of the random Gaussian feature extraction.
static java.lang.String	getMARFSourceCodeRevision() Returns source code revision information.

Methods inherited from class marf.FeatureExtraction.FeatureExtraction

backSynchronizeObject, clone, getFeaturesArray, getPreprocessing, setPreprocessing

Methods inherited from class marf.Storage.StorageManager

dump, dumpBinary, dumpCSV, dumpGzipBinary, dumpHTML, dumpSQL, dumpXML, enableDumpOnNotFound, equals, getDefaultExtension, getDefaultExtension, getDumpMode, getFilename, getObjectToSerialize, hashCode, restore, restoreBinary, restoreCSV, restoreGzipBinary, restoreHTML, restoreSQL, restoreXML, setDumpMode, setFilename, toString

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Field Detail

DEFAULT_CHUNK_SIZE

public static final int DEFAULT_CHUNK_SIZE

Default number (256) of doubles per chunk in a feature vector.

See Also:

Constant Field Values

serialVersionUID

private static final long serialVersionUID

For serialization versioning. When adding new members or make other structural changes regenerate this number with the serialver tool that comes with JDK.

Since:

0.3.0.4

See Also:

Constant Field Values

Constructor Detail

RandomFeatureExtraction

public RandomFeatureExtraction(IPreprocessing poPreprocessing)

RandomFeatureExtraction Constructor.

Parameters:

poPreprocessing - Preprocessing object reference

Method Detail

extractFeatures

public final boolean extractFeatures()
                              throws FeatureExtractionException

Random Gaussian-based feature extraction. Sample is taken from an IPreprocessing module from the pipeline.

Specified by:

extractFeatures in interface IFeatureExtraction

Overrides:

extractFeatures in class FeatureExtraction

Returns:

true if successful

Throws:

FeatureExtractionException - in case of any error

See Also:

IFeatureExtraction.extractFeatures()

extractFeatures

public final boolean extractFeatures(double[] padSampleData)
                              throws FeatureExtractionException

Extracts features from the provided sample array.

Parameters:

padSampleData - the sample to extract features from

Returns:

boolean true if there were features extracted, false otherwise

Throws:

FeatureExtractionException - if there was an error while extracting features

Since:

0.3.0.6

See Also:

IFeatureExtraction.extractFeatures(double[])

extractFeaturesImplementation

protected final boolean extractFeaturesImplementation(Sample poSample)
                                               throws FeatureExtractionException

Does the actual business logic of the random Gaussian feature extraction.

Parameters:

poSample - sample to extract features from

Returns:

true if there were features extracted, false otherwise

Throws:

FeatureExtractionException - in case of any errors while doing stuff

Since:

0.3.0.6

getMARFSourceCodeRevision

public static java.lang.String getMARFSourceCodeRevision()

Returns source code revision information.

Returns:

revision string

Since:

0.3.0.2