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. |
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 |
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
RandomFeatureExtraction
public RandomFeatureExtraction(IPreprocessing poPreprocessing)
- RandomFeatureExtraction Constructor.
- Parameters:
poPreprocessing
- Preprocessing object reference
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