| java.lang.Object
 weka.attributeSelection.ASSearch
weka.attributeSelection.FCBFSearch
| FCBFSearch | | public class FCBFSearch extends ASSearch implements RankedOutputSearch,StartSetHandler,OptionHandler,TechnicalInformationHandler(Code) | |
FCBF :
Feature selection method based on correlation measureand relevance&redundancy analysis. Use in conjunction with an attribute set evaluator (SymmetricalUncertAttributeEval).
For more information see:
Lei Yu, Huan Liu: Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution. In: Proceedings of the Twentieth International Conference on Machine Learning, 856-863, 2003.
BibTeX:
@inproceedings{Yu2003,
author = {Lei Yu and Huan Liu},
booktitle = {Proceedings of the Twentieth International Conference on Machine Learning},
pages = {856-863},
publisher = {AAAI Press},
title = {Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution},
year = {2003}
}
Valid options are:
-D <create dataset>
Specify Whether the selector generates a new dataset.
-P <start set>
Specify a starting set of attributes.
Eg. 1,3,5-7.
Any starting attributes specified are
ignored during the ranking.
-T <threshold>
Specify a theshold by which attributes
may be discarded from the ranking.
-N <num to select>
Specify number of attributes to select
author:
Zheng Zhao: zhaozheng at asu.edu
version:
$Revision: 1.6 $ |
| serialVersionUID | | final static long serialVersionUID(Code) | | for serialization
|
| FCBFSearch | | public FCBFSearch()(Code) | | Constructor
|
| generateDataOutputTipText | | public String generateDataOutputTipText()(Code) | | Returns the tip text for this property
tip text for this property suitable fordisplaying in the explorer/experimenter gui |
| generateRankingTipText | | public String generateRankingTipText()(Code) | | Returns the tip text for this property
tip text for this property suitable fordisplaying in the explorer/experimenter gui |
| getCalculatedNumToSelect | | public int getCalculatedNumToSelect()(Code) | | Gets the calculated number to select. This might be computed
from a threshold, or if < 0 is set as the number to select then
it is set to the number of attributes in the (transformed) data.
the calculated number of attributes to select |
| getGenerateDataOutput | | public boolean getGenerateDataOutput()(Code) | | Returns the flag, by which the AttributeSelection module decide
whether create a new dataset according to the selected features.
the flag, by which the AttributeSelection module decidewhether create a new dataset according to the selected features. |
| getGenerateRanking | | public boolean getGenerateRanking()(Code) | | This is a dummy method. Ranker can ONLY be used with attribute
evaluators and as such can only produce a ranked list of attributes
true all the time. |
| getNumToSelect | | public int getNumToSelect()(Code) | | Gets the number of attributes to be retained.
the number of attributes to retain |
| getOptions | | public String[] getOptions()(Code) | | Gets the current settings of ReliefFAttributeEval.
an array of strings suitable for passing to setOptions() |
| getStartSet | | public String getStartSet()(Code) | | Returns a list of attributes (and or attribute ranges) as a String
a list of attributes (and or attribute ranges) |
| getTechnicalInformation | | public TechnicalInformation getTechnicalInformation()(Code) | | 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.
the technical information about this class |
| getThreshold | | public double getThreshold()(Code) | | Returns the threshold so that the AttributeSelection module can
discard attributes from the ranking.
the threshold |
| globalInfo | | public String globalInfo()(Code) | | Returns a string describing this search method
a description of the search suitable fordisplaying in the explorer/experimenter gui |
| listOptions | | public Enumeration listOptions()(Code) | | Returns an enumeration describing the available options.
an enumeration of all the available options. |
| numToSelectTipText | | public String numToSelectTipText()(Code) | | Returns the tip text for this property
tip text for this property suitable fordisplaying in the explorer/experimenter gui |
| rankedAttributes | | public double[][] rankedAttributes() throws Exception(Code) | | Sorts the evaluated attribute list
an array of sorted (highest eval to lowest) attribute indexes
throws:
Exception - of sorting can't be done. |
| resetOptions | | protected void resetOptions()(Code) | | Resets stuff to default values
|
| search | | public int[] search(ASEvaluation ASEval, Instances data) throws Exception(Code) | | Kind of a dummy search algorithm. Calls a Attribute evaluator to
evaluate each attribute not included in the startSet and then sorts
them to produce a ranked list of attributes.
Parameters:
ASEval - the attribute evaluator to guide the search
Parameters:
data - the training instances. an array (not necessarily ordered) of selected attribute indexes
throws:
Exception - if the search can't be completed |
| setGenerateDataOutput | | public void setGenerateDataOutput(boolean doGenerate)(Code) | | Sets the flag, by which the AttributeSelection module decide
whether create a new dataset according to the selected features.
Parameters:
doGenerate - the flag, by which the AttributeSelection moduledecide whether create a new dataset according to the selectedfeatures |
| setGenerateRanking | | public void setGenerateRanking(boolean doRank)(Code) | | This is a dummy set method---Ranker is ONLY capable of producing
a ranked list of attributes for attribute evaluators.
Parameters:
doRank - this parameter is N/A and is ignored |
| setNumToSelect | | public void setNumToSelect(int n)(Code) | | Specify the number of attributes to select from the ranked list. -1
indicates that all attributes are to be retained.
Parameters:
n - the number of attributes to retain |
| setOptions | | public void setOptions(String[] options) throws Exception(Code) | | Parses a given list of options.
Valid options are:
-D <create dataset>
Specify Whether the selector generates a new dataset.
-P <start set>
Specify a starting set of attributes.
Eg. 1,3,5-7.
Any starting attributes specified are
ignored during the ranking.
-T <threshold>
Specify a theshold by which attributes
may be discarded from the ranking.
-N <num to select>
Specify number of attributes to select
Parameters:
options - the list of options as an array of strings
throws:
Exception - if an option is not supported |
| setStartSet | | public void setStartSet(String startSet) throws Exception(Code) | | Sets a starting set of attributes for the search. It is the
search method's responsibility to report this start set (if any)
in its toString() method.
Parameters:
startSet - a string containing a list of attributes (and or ranges),eg. 1,2,6,10-15.
throws:
Exception - if start set can't be set. |
| setThreshold | | public void setThreshold(double threshold)(Code) | | Set the threshold by which the AttributeSelection module can discard
attributes.
Parameters:
threshold - the threshold. |
| startSetTipText | | public String startSetTipText()(Code) | | Returns the tip text for this property
tip text for this property suitable fordisplaying in the explorer/experimenter gui |
| thresholdTipText | | public String thresholdTipText()(Code) | | Returns the tip text for this property
tip text for this property suitable fordisplaying in the explorer/experimenter gui |
| toString | | public String toString()(Code) | | returns a description of the search as a String
a description of the search |
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