public class myDataset
extends java.lang.Object
Title: Dataset
Description: It contains the methods to read a Classification/Regression Dataset
Company: KEEL
Modifier and Type | Field and Description |
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static int |
INTEGER
Number to represent type of variable integer.
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static int |
NOMINAL
Number to represent type of variable nominal.
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static int |
REAL
Number to represent type of variable real or double.
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Constructor and Description |
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myDataset()
Init a new set of instances
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Modifier and Type | Method and Description |
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double |
average(int position)
It return the average of an specific attribute
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void |
computeInstancesPerClass()
It computes the number the instances per class.
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java.lang.String |
copyHeader()
It copies the header of the dataset
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double[][] |
devuelveRangos()
Returns the minimum and maximum values of every attributes as a matrix.
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void |
discretize(int intervalos)
Uniform width discretization
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double[] |
getemax()
It returns an array with the maximum values of the attributes
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double[] |
getemin()
It returns an array with the minimum values of the attributes
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double[] |
getExample(int pos)
Output a specific example
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double |
getMax(int variable)
It returns the maximum value of the attribute specified
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double |
getMin(int variable)
It returns the minimum value of the attribute specified
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int |
getnClasses()
It gets the number of output attributes of the data-set (for example number of classes in classification)
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int |
getnData()
It gets the size of the data-set
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int |
getnInputs()
It gets the number of input attributes of the data-set
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int |
getnVars()
It gets the number of variables of the data-set (including the output)
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int[] |
getOutputAsInteger()
Returns the output of the data-set as integer values
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int |
getOutputAsInteger(int pos)
It returns the output value of the example "pos"
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double[] |
getOutputAsReal()
Returns the output of the data-set as real values
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double |
getOutputAsReal(int pos)
It returns the output value of the example "pos"
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java.lang.String[] |
getOutputAsString()
Returns the output of the data-set as nominal values
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java.lang.String |
getOutputAsString(int pos)
It returns the output value of the example "pos"
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java.lang.String |
getOutputValue(int intValue)
It returns the name of the class of index intValue
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int |
getTipo(int variable)
It returns the type of the attribute specified
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double[][] |
getX()
Outputs an array of examples with their corresponding attribute values.
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boolean |
hasMissingAttributes()
It checks if the data-set has any missing value
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boolean |
hasNumericalAttributes()
It checks if the data-set has any numerical value
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boolean |
hasRealAttributes()
It checks if the data-set has any real value
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boolean |
isMissing(int i,
int j)
This function checks if the attribute value is missing
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java.lang.String |
nombreClase(int clase)
It returns the name of the class of index intValue
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java.lang.String[] |
nombres()
It returns the name of the attributes
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java.lang.String |
nombreVar(int pos)
Returns the name of the attribute with the id given.
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void |
normalize()
It transform the input space into the [0,1] range
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int |
numberInstances(int clas)
It returns the number of instances in the dataset of the given class
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int |
numberValues(int attribute)
It returns the number of different values of an attribute
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void |
readClassificationSet(java.lang.String datasetFile,
boolean train)
It reads the whole input data-set and it stores each example and its associated output value in
local arrays to ease their use.
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void |
readRegressionSet(java.lang.String datasetFile,
boolean train)
It reads the whole input data-set and it stores each example and its associated output value in
local arrays to ease their use.
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int |
size()
It returns the number of examples
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int |
sizeWithoutMissing()
It return the size of the data-set without having account the missing values
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double |
stdDev(int position)
It return the standard deviation of an specific attribute
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int |
sumMinorityClasses()
Returns the summation of the number of instances that belong to the minority classes
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public static final int REAL
public static final int INTEGER
public static final int NOMINAL
public double[][] getX()
public double[] getExample(int pos)
pos
- int position (id) of the example in the data-setpublic int[] getOutputAsInteger()
public double[] getOutputAsReal()
public java.lang.String[] getOutputAsString()
public java.lang.String getOutputAsString(int pos)
pos
- int the position (id) of the examplepublic int getOutputAsInteger(int pos)
pos
- int the position (id) of the examplepublic double getOutputAsReal(int pos)
pos
- int the position (id) of the examplepublic double[] getemax()
public double[] getemin()
public double getMax(int variable)
variable
- index of the attributepublic double getMin(int variable)
variable
- index of the attributepublic int getnData()
public int getnVars()
public int getnInputs()
public int getnClasses()
public boolean isMissing(int i, int j)
i
- int Example idj
- int Variable idpublic void readClassificationSet(java.lang.String datasetFile, boolean train) throws java.io.IOException
datasetFile
- String name of the file containing the datasettrain
- boolean It must have the value "true" if we are reading the training data-setjava.io.IOException
- If there ocurs any problem with the reading of the data-setpublic void readRegressionSet(java.lang.String datasetFile, boolean train) throws java.io.IOException
datasetFile
- String name of the file containing the datasettrain
- boolean It must have the value "true" if we are reading the training data-setjava.io.IOException
- If there ocurs any problem with the reading of the data-setpublic java.lang.String copyHeader()
public void normalize()
public boolean hasRealAttributes()
public boolean hasNumericalAttributes()
public boolean hasMissingAttributes()
public int sizeWithoutMissing()
public int size()
public double stdDev(int position)
position
- int attribute id (position of the attribute)public double average(int position)
position
- int attribute id (position of the attribute)public void computeInstancesPerClass()
public int numberInstances(int clas)
clas
- the index of the classpublic int numberValues(int attribute)
attribute
- the index of the attributepublic java.lang.String getOutputValue(int intValue)
intValue
- the index of the classpublic int getTipo(int variable)
variable
- index of the attributepublic double[][] devuelveRangos()
public java.lang.String nombreVar(int pos)
pos
- attribute's id.public java.lang.String nombreClase(int clase)
clase
- the index of the classpublic void discretize(int intervalos)
intervalos
- int Number of intervalspublic java.lang.String[] nombres()
public int sumMinorityClasses()