public class MIEMDD extends RandomizableClassifier implements OptionHandler, MultiInstanceCapabilitiesHandler, TechnicalInformationHandler
@inproceedings{Zhang2001, author = {Qi Zhang and Sally A. Goldman}, booktitle = {Advances in Neural Information Processing Systems 14}, pages = {1073-108}, publisher = {MIT Press}, title = {EM-DD: An Improved Multiple-Instance Learning Technique}, year = {2001} }Valid options are:
-N <num> Whether to 0=normalize/1=standardize/2=neither. (default 1=standardize)
-S <num> Random number seed. (default 1)
-D If set, classifier is run in debug mode and may output additional info to the console
Modifier and Type | Field and Description |
---|---|
static int |
FILTER_NONE
No normalization/standardization
|
static int |
FILTER_NORMALIZE
Normalize training data
|
static int |
FILTER_STANDARDIZE
Standardize training data
|
protected Instances |
m_Attributes
All attribute names
|
protected int[] |
m_Classes
Class labels for each bag
|
protected int |
m_ClassIndex
The index of the class attribute
|
protected double[][][] |
m_Data
MI data
|
protected double[][] |
m_emData
MI data
|
protected Filter |
m_Filter
The filter used to standardize/normalize all values.
|
protected int |
m_filterType
Whether to normalize/standardize/neither, default:standardize
|
protected ReplaceMissingValues |
m_Missing
The filter used to get rid of missing values.
|
protected int |
m_NumClasses
The number of the class labels
|
protected double[] |
m_Par |
static Tag[] |
TAGS_FILTER
The filter to apply to the training data
|
m_Seed
m_Debug
Constructor and Description |
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MIEMDD() |
Modifier and Type | Method and Description |
---|---|
void |
buildClassifier(Instances train)
Builds the classifier
|
double[] |
distributionForInstance(Instance exmp)
Computes the distribution for a given exemplar
|
String |
filterTypeTipText()
Returns the tip text for this property
|
protected int |
findInstance(int i,
double[] x)
given x, find the instance in ith bag with the most likelihood
probability, which is most likely to responsible for the label of the
bag For a positive bag, find the instance with the maximal probability
of being positive For a negative bag, find the instance with the minimal
probability of being negative
|
Capabilities |
getCapabilities()
Returns default capabilities of the classifier.
|
SelectedTag |
getFilterType()
Gets how the training data will be transformed.
|
Capabilities |
getMultiInstanceCapabilities()
Returns the capabilities of this multi-instance classifier for the
relational data.
|
String[] |
getOptions()
Gets the current settings of the classifier.
|
String |
getRevision()
Returns the revision string.
|
TechnicalInformation |
getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing
detailed information about the technical background of this class,
e.g., paper reference or book this class is based on.
|
String |
globalInfo()
Returns a string describing this filter
|
Enumeration |
listOptions()
Returns an enumeration describing the available options
|
static void |
main(String[] argv)
Main method for testing this class.
|
void |
setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
setOptions(String[] options)
Parses a given list of options.
|
String |
toString()
Gets a string describing the classifier.
|
getSeed, seedTipText, setSeed
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, runClassifier, setDebug
protected int m_ClassIndex
protected double[] m_Par
protected int m_NumClasses
protected int[] m_Classes
protected double[][][] m_Data
protected Instances m_Attributes
protected double[][] m_emData
protected Filter m_Filter
protected int m_filterType
public static final int FILTER_NORMALIZE
public static final int FILTER_STANDARDIZE
public static final int FILTER_NONE
public static final Tag[] TAGS_FILTER
protected ReplaceMissingValues m_Missing
public String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class RandomizableClassifier
public void setOptions(String[] options) throws Exception
-N <num> Whether to 0=normalize/1=standardize/2=neither. (default 1=standardize)
-S <num> Random number seed. (default 1)
-D If set, classifier is run in debug mode and may output additional info to the console
setOptions
in interface OptionHandler
setOptions
in class RandomizableClassifier
options
- the list of options as an array of stringsException
- if an option is not supportedpublic String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class RandomizableClassifier
public String filterTypeTipText()
public SelectedTag getFilterType()
public void setFilterType(SelectedTag newType)
newType
- the new filtering modepublic Capabilities getCapabilities()
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class Classifier
Capabilities
public Capabilities getMultiInstanceCapabilities()
getMultiInstanceCapabilities
in interface MultiInstanceCapabilitiesHandler
Capabilities
public void buildClassifier(Instances train) throws Exception
buildClassifier
in class Classifier
train
- the training data to be used for generating the
boosted classifier.Exception
- if the classifier could not be built successfullyprotected int findInstance(int i, double[] x)
i
- the bag indexx
- the current values of variablespublic double[] distributionForInstance(Instance exmp) throws Exception
distributionForInstance
in class Classifier
exmp
- the exemplar for which distribution is computedException
- if the distribution can't be computed successfullypublic String toString()
public String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class Classifier
public static void main(String[] argv)
argv
- should contain the command line arguments to the
scheme (see Evaluation)Copyright © 2015 University of Waikato, Hamilton, NZ. All rights reserved.