public abstract class FuzzyIBLAlgorithm
extends java.lang.Object
Modifier and Type | Field and Description |
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protected int |
inputAtt
Number of input attributes.
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protected Attribute[] |
inputs
Training size.
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protected java.lang.String |
name
Algorithm name.
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protected int |
nClasses
Number of classes.
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protected int[] |
nInstances
Number of instances of each classes.
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protected boolean[] |
nominal
Identifies the nominal attributes.
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protected boolean[] |
nulls
Missing values of a instance.
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protected java.lang.String[] |
outFile
Output files names.
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protected Attribute |
output
Output attribute.
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protected InstanceSet |
reference
Reference dataset.
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protected double[][] |
referenceData
Reference input data.
|
protected java.lang.String |
referenceFile
Reference file name.
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protected int[] |
referenceOutput
Reference output data.
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protected java.lang.String |
relation
Relation string.
|
protected long |
seed
Random seed.
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protected Instance |
temp
Temporal instance.
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protected InstanceSet |
test
Test dataset.
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protected double[][] |
testData
Test input data.
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protected java.lang.String |
testFile
Test file name.
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protected int[] |
testOutput
Test output data.
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protected int[] |
testPrediction
Predicted classes for the test dataset.
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protected InstanceSet |
train
Training dataset.
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protected double[][] |
trainData
Training input data.
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protected java.lang.String |
trainFile
Train file name.
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protected int[] |
trainOutput
Training output data.
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protected int[] |
trainPrediction
Predicted classes for the training dataset.
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protected int |
trainSize
Training size.
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Constructor and Description |
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FuzzyIBLAlgorithm() |
Modifier and Type | Method and Description |
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protected void |
normalizeReference()
This function builds the data matrix for reference data and normalizes inputs values
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protected void |
normalizeTest()
This function builds the data matrix for test data and normalizes inputs values
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protected void |
normalizeTrain()
This function builds the data matrix for training data and normalizes inputs values
|
protected void |
readConfiguracion(java.lang.String script)
Reads configuration script, and extracts its contents.
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protected void |
readDataFiles(java.lang.String script)
Read the configuration and data files, and process it.
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protected abstract void |
readParameters(java.lang.String script)
Reads the parameters of the algorithm.
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protected void |
writeOutput(java.lang.String filename,
int[] realClass,
int[] prediction)
Prints KEEL standard output files.
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protected java.lang.String[] outFile
protected java.lang.String testFile
protected java.lang.String trainFile
protected java.lang.String referenceFile
protected InstanceSet train
protected InstanceSet test
protected InstanceSet reference
protected Instance temp
protected int inputAtt
protected int trainSize
protected Attribute[] inputs
protected Attribute output
protected boolean[] nulls
protected boolean[] nominal
protected double[][] trainData
protected int[] trainOutput
protected double[][] testData
protected int[] testOutput
protected double[][] referenceData
protected int[] referenceOutput
protected java.lang.String relation
protected int nClasses
protected int[] nInstances
protected java.lang.String name
protected long seed
protected int[] trainPrediction
protected int[] testPrediction
protected void readDataFiles(java.lang.String script)
script
- Name of the configuration scriptprotected void readConfiguracion(java.lang.String script)
script
- Name of the configuration scriptprotected abstract void readParameters(java.lang.String script)
script
- Configuration scriptprotected void normalizeTrain() throws DataException
DataException
- if the dataset is not appropiated for the algorithm.protected void normalizeTest() throws DataException
DataException
- if the dataset is not appropiated for the algorithm.protected void normalizeReference() throws DataException
DataException
- if the dataset is not appropiated for the algorithm.protected void writeOutput(java.lang.String filename, int[] realClass, int[] prediction)
filename
- Name of output filerealClass
- Real output of instancesprediction
- Predicted output for instances