keel.Algorithms.Decision_Trees.DT_oblicuo

Class myDataset

java.lang.Object

keel.Algorithms.Decision_Trees.DT_oblicuo.myDataset

public class myDataset
extends java.lang.Object

It contains the methods to read a Classification/Regression Dataset

Since:

JDK1.6

Version:

1.0

Author:

Alberto Fernández

Field Summary

Fields

Modifier and Type	Field and Description
static int	INTEGER Number to represent type of variable integer.
static int	NOMINAL Number to represent type of variable nominal.
static int	REAL Number to represent type of variable real or double.

Constructor Summary

Constructors

Constructor and Description
myDataset() Init a new set of instances

Method Summary

Modifier and Type	Method and Description
double	average(int position) It return the average of an specific attribute
java.lang.String	claseMasFrecuente() It returns the most frequent class in the dataset
void	computeInstancesPerClass() It computes the number the instances per class.
java.lang.String	copyHeader() It copies the header of the dataset
double[][]	devuelveRangos() Returns the minimum and maximum values of every attributes as a matrix.
void	discretize(int intervalos) Uniform width discretization
boolean	esNominal(int atributo) This function checks if the attribute value is nominal
double[]	getemax() It returns an array with the maximum values of the attributes
double[]	getemin() It returns an array with the minimum values of the attributes
double[]	getExample(int pos) Output a specific example
double	getMax(int variable) It returns the maximum value of the attribute specified
double	getMin(int variable) It returns the minimum value of the attribute specified
int	getnClasses() It gets the number of output attributes of the data-set (for example number of classes in classification)
int	getnData() It gets the size of the data-set
int	getnInputs() It gets the number of input attributes of the data-set
int	getnVars() It gets the number of variables of the data-set (including the output)
int[]	getOutputAsInteger() Returns the output of the data-set as integer values
int	getOutputAsInteger(int pos) It returns the output value of the example "pos"
double[]	getOutputAsReal() Returns the output of the data-set as real values
double	getOutputAsReal(int pos) It returns the output value of the example "pos"
java.lang.String[]	getOutputAsString() Returns the output of the data-set as nominal values
java.lang.String	getOutputAsString(int pos) It returns the output value of the example "pos"
java.lang.String	getOutputValue(int intValue) It returns the name of the class of index intValue
int	getTipo(int variable) It returns the type of the attribute specified
double[][]	getX() Outputs an array of examples with their corresponding attribute values.
boolean	hasMissingAttributes() It checks if the data-set has any missing value
boolean	hasNominalAttributes() It checks if the data-set has any nominal value
boolean	hasNumericalAttributes() It checks if the data-set has any numerical value
boolean	hasRealAttributes() It checks if the data-set has any real value
boolean	isMissing(int i, int j) This function checks if the attribute value is missing
java.lang.String	nombreClase(int clase) It returns the name of the class of index intValue
java.lang.String[]	nombres() It returns the name of the attributes
java.lang.String	nombreVar(int pos) Returns the name of the attribute with the id given.
void	normalize() It transform the input space into the [0,1] range
int	numberInstances(int clas) It returns the number of instances in the dataset of the given class
int	numberValues(int attribute) It returns the number of different values of an attribute
int	numEjemplos(int clase) It returns the number of instances in the dataset of the given class
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.
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.
int	size() It returns the number of examples
int	sizeWithoutMissing() It return the size of the data-set without having account the missing values
double	stdDev(int position) It return the standard deviation of an specific attribute
int	totalNominales(int atributo) It returns the number of nominal values for a given variable
int	totalValores(int atributo) Function to get the number of different feasible values for a given attribute
double	valor(int atributo, int pos) Returns the value of a given attribute in a given position (id).
static java.lang.String	valorNominal(int atributo, double valorReal) Returns a nominal representation of a attribute's real value given as argument.
static double	valorReal(int atributo, java.lang.String valorNominal) Returns a real representation of a attribute's nominal value given as argument.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

REAL

public static final int REAL

Number to represent type of variable real or double.

See Also:

Constant Field Values

INTEGER

public static final int INTEGER

Number to represent type of variable integer.

See Also:

Constant Field Values

NOMINAL

public static final int NOMINAL

Number to represent type of variable nominal.

See Also:

Constant Field Values

Constructor Detail

myDataset

public myDataset()

Init a new set of instances

Method Detail

getX

public double[][] getX()

Outputs an array of examples with their corresponding attribute values.

Returns:

double[][] an array of examples with their corresponding attribute values

getExample

public double[] getExample(int pos)

Output a specific example

Parameters:

pos - int position (id) of the example in the data-set

Returns:

double[] the attributes of the given example

getOutputAsInteger

public int[] getOutputAsInteger()

Returns the output of the data-set as integer values

Returns:

int[] an array of integer values corresponding to the output values of the dataset

getOutputAsReal

public double[] getOutputAsReal()

Returns the output of the data-set as real values

Returns:

double[] an array of real values corresponding to the output values of the dataset

getOutputAsString

public java.lang.String[] getOutputAsString()

Returns the output of the data-set as nominal values

Returns:

String[] an array of nomianl values corresponding to the output values of the dataset

getOutputAsString

public java.lang.String getOutputAsString(int pos)

It returns the output value of the example "pos"

Parameters:

pos - int the position (id) of the example

Returns:

String a string containing the output value

getOutputAsInteger

public int getOutputAsInteger(int pos)

It returns the output value of the example "pos"

Parameters:

pos - int the position (id) of the example

Returns:

int an integer containing the output value

getOutputAsReal

public double getOutputAsReal(int pos)

It returns the output value of the example "pos"

Parameters:

pos - int the position (id) of the example

Returns:

double a real containing the output value

getemax

public double[] getemax()

It returns an array with the maximum values of the attributes

Returns:

double[] an array with the maximum values of the attributes

getemin

public double[] getemin()

It returns an array with the minimum values of the attributes

Returns:

double[] an array with the minimum values of the attributes

getMax

public double getMax(int variable)

It returns the maximum value of the attribute specified

Parameters:

variable - index of the attribute

Returns:

the maximum value of the attribute

getMin

public double getMin(int variable)

It returns the minimum value of the attribute specified

Parameters:

variable - index of the attribute

Returns:

the minimum value of the attribute

getnData

public int getnData()

It gets the size of the data-set

Returns:

int the number of examples in the data-set

getnVars

public int getnVars()

It gets the number of variables of the data-set (including the output)

Returns:

int the number of variables of the data-set (including the output)

getnInputs

public int getnInputs()

It gets the number of input attributes of the data-set

Returns:

int the number of input attributes of the data-set

getnClasses

public int getnClasses()

It gets the number of output attributes of the data-set (for example number of classes in classification)

Returns:

int the number of different output values of the data-set

isMissing

public boolean isMissing(int i,
                         int j)

This function checks if the attribute value is missing

Parameters:

i - int Example id

j - int Variable id

Returns:

boolean True is the value is missing, else it returns false

readClassificationSet

public void readClassificationSet(java.lang.String datasetFile,
                                  boolean train)
                           throws java.io.IOException

It reads the whole input data-set and it stores each example and its associated output value in local arrays to ease their use.

Parameters:

datasetFile - String name of the file containing the dataset

train - boolean It must have the value "true" if we are reading the training data-set

Throws:

java.io.IOException - If there ocurs any problem with the reading of the data-set

readRegressionSet

public void readRegressionSet(java.lang.String datasetFile,
                              boolean train)
                       throws java.io.IOException

It reads the whole input data-set and it stores each example and its associated output value in local arrays to ease their use.

Parameters:

datasetFile - String name of the file containing the dataset

train - boolean It must have the value "true" if we are reading the training data-set

Throws:

java.io.IOException - If there ocurs any problem with the reading of the data-set

copyHeader

public java.lang.String copyHeader()

It copies the header of the dataset

Returns:

String A string containing all the data-set information

normalize

public void normalize()

It transform the input space into the [0,1] range

hasRealAttributes

public boolean hasRealAttributes()

It checks if the data-set has any real value

Returns:

boolean True if it has some real values, else false.

hasNumericalAttributes

public boolean hasNumericalAttributes()

It checks if the data-set has any numerical value

Returns:

boolean True if it has some numerical values, else false.

hasNominalAttributes

public boolean hasNominalAttributes()

It checks if the data-set has any nominal value

Returns:

boolean True if it has some nominal values, else false.

hasMissingAttributes

public boolean hasMissingAttributes()

It checks if the data-set has any missing value

Returns:

boolean True if it has some missing values, else false.

sizeWithoutMissing

public int sizeWithoutMissing()

It return the size of the data-set without having account the missing values

Returns:

int the size of the data-set without having account the missing values

size

public int size()

It returns the number of examples

Returns:

the number of examples

stdDev

public double stdDev(int position)

It return the standard deviation of an specific attribute

Parameters:

position - int attribute id (position of the attribute)

Returns:

double the standard deviation of the attribute

average

public double average(int position)

It return the average of an specific attribute

Parameters:

position - int attribute id (position of the attribute)

Returns:

double the average of the attribute

computeInstancesPerClass

public void computeInstancesPerClass()

It computes the number the instances per class.

numberInstances

public int numberInstances(int clas)

It returns the number of instances in the dataset of the given class

Parameters:

clas - the index of the class

Returns:

the number of instances in the dataset of the given class

numberValues

public int numberValues(int attribute)

It returns the number of different values of an attribute

Parameters:

attribute - the index of the attribute

Returns:

the number of different values of an attribute

getOutputValue

public java.lang.String getOutputValue(int intValue)

It returns the name of the class of index intValue

Parameters:

intValue - the index of the class

Returns:

the name of the class of index intValue

getTipo

public int getTipo(int variable)

It returns the type of the attribute specified

Parameters:

variable - index of the attribute

Returns:

the type of the attribute specified

devuelveRangos

public double[][] devuelveRangos()

Returns the minimum and maximum values of every attributes as a matrix. The matrix has a size of number_of_attributes x 2 ([nAttributes][2]). The minimum value is located at the first position of each array and the maximum, at the second.

Returns:

Matrix which stores the minimum and maximum values of every attributes.

nombreVar

public java.lang.String nombreVar(int pos)

Returns the name of the attribute with the id given.

Parameters:

pos - attribute's id.

Returns:

name of the attribute.

nombreClase

public java.lang.String nombreClase(int clase)

It returns the name of the class of index intValue

Parameters:

clase - the index of the class

Returns:

the name of the class of index intValue

discretize

public void discretize(int intervalos)

Uniform width discretization

Parameters:

intervalos - int Number of intervals

nombres

public java.lang.String[] nombres()

It returns the name of the attributes

Returns:

the name of the attributes

valorReal

public static double valorReal(int atributo,
                               java.lang.String valorNominal)

Returns a real representation of a attribute's nominal value given as argument.

Parameters:

atributo - Attribute given.

valorNominal - Nominal value of the attribute given.

Returns:

Returns a real representation of a attribute's nominal value.

valorNominal

public static java.lang.String valorNominal(int atributo,
                                            double valorReal)

Returns a nominal representation of a attribute's real value given as argument.

Parameters:

atributo - Attribute given.

valorReal - Real value of the attribute given.

Returns:

Returns a nominal representation of a attribute's real value.

totalNominales

public int totalNominales(int atributo)

It returns the number of nominal values for a given variable

Parameters:

atributo - variable id

Returns:

the number of nominal values for a given variable

claseMasFrecuente

public java.lang.String claseMasFrecuente()

It returns the most frequent class in the dataset

Returns:

the most frequent class in the dataset

numEjemplos

public int numEjemplos(int clase)

It returns the number of instances in the dataset of the given class

Parameters:

clase - the index of the class

Returns:

the number of instances in the dataset of the given class

esNominal

public boolean esNominal(int atributo)

This function checks if the attribute value is nominal

Parameters:

atributo - attribute id

Returns:

boolean True is the value is nominal, else it returns false

totalValores

public int totalValores(int atributo)

Function to get the number of different feasible values for a given attribute

Parameters:

atributo - int Given attribute

Returns:

int Number of different feasible values for a given attribute

valor

public double valor(int atributo,
                    int pos)

Returns the value of a given attribute in a given position (id).

Parameters:

atributo - given attribute.

pos - given ID of the value.

Returns:

the value of the given attribute.