water.genmodel

Class GeneratedModel

java.lang.Object

water.genmodel.GeneratedModel

All Implemented Interfaces:

IGeneratedModel

public abstract class GeneratedModel
extends java.lang.Object
implements IGeneratedModel

This is a helper class to support Java generated models.

Constructor Summary

Constructors

Constructor and Description
GeneratedModel()

Method Summary

Methods

Modifier and Type	Method and Description
int	getColIdx(java.lang.String name) Returns index of column with give name or -1 if column is not found.
java.lang.String[]	getDomainValues(int i) Returns domain values for i-th column.
java.lang.String[]	getDomainValues(java.lang.String name) Gets domain of given column.
java.lang.String	getHeader()
int	getNumClasses(int i) Get number of classes in in given column.
int	getNumCols() Returns number of columns used as input for training (i.e., exclude response column).
int	getNumResponseClasses() Return a number of classes in response column.
int	getPredsSize() Returns the expected size of preds array which is passed to IGeneratedModel.predict(double[], float[]) function.
int	getResponseIdx() Returns an index of the response column.
java.lang.String	getResponseName() The name of the response column.
static boolean	grpContains(byte[] gcmp, int offset, int idx) Return true if the given index is in given bit array else false.
boolean	isAutoEncoder()
boolean	isClassifier() Return true if this model represents a classifier, else it is used for regression.
double[]	map(java.util.Map<java.lang.String,java.lang.Double> row, double[] data) Takes a HashMap mapping column names to doubles.
int	mapEnum(int colIdx, java.lang.String enumValue) Maps given column's enum to integer used by this model.
float[]	predict(java.util.Map<java.lang.String,java.lang.Double> row)
float[]	predict(java.util.Map<java.lang.String,java.lang.Double> row, double[] data, float[] preds)
float[]	predict(java.util.Map<java.lang.String,java.lang.Double> row, float[] preds)

Methods inherited from class java.lang.Object

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

Methods inherited from interface water.genmodel.IGeneratedModel

getDomainValues, getNames, getUUID, predict, predict

Constructor Detail

GeneratedModel

public GeneratedModel()

Method Detail

getNumCols

public int getNumCols()

Description copied from interface: IGeneratedModel

Returns number of columns used as input for training (i.e., exclude response column).

Specified by:

getNumCols in interface IGeneratedModel

getResponseIdx

public int getResponseIdx()

Description copied from interface: IGeneratedModel

Returns an index of the response column.

Specified by:

getResponseIdx in interface IGeneratedModel

getResponseName

public java.lang.String getResponseName()

Description copied from interface: IGeneratedModel

The name of the response column.

Specified by:

getResponseName in interface IGeneratedModel

getNumResponseClasses

public int getNumResponseClasses()

Description copied from interface: IGeneratedModel

Return a number of classes in response column.

Specified by:

getNumResponseClasses in interface IGeneratedModel

isClassifier

public boolean isClassifier()

Description copied from interface: IGeneratedModel

Return true if this model represents a classifier, else it is used for regression.

Specified by:

isClassifier in interface IGeneratedModel

grpContains

public static boolean grpContains(byte[] gcmp,
                  int offset,
                  int idx)

Return true if the given index is in given bit array else false.

The method returns false if idx is less than offset. It also returns false if the idx is greater then length of given bit set!

Parameters:

gcmp - bit set array

offset - number of bits skipped by default since there are 0

idx - index of bit to be checked if it is in bitset

Returns:

getHeader

public java.lang.String getHeader()

isAutoEncoder

public boolean isAutoEncoder()

getColIdx

public int getColIdx(java.lang.String name)

Description copied from interface: IGeneratedModel

Returns index of column with give name or -1 if column is not found.

Specified by:

getColIdx in interface IGeneratedModel

getNumClasses

public int getNumClasses(int i)

Description copied from interface: IGeneratedModel

Get number of classes in in given column. Return number greater than zero if the column is categorical or -1 if the column is numeric.

Specified by:

getNumClasses in interface IGeneratedModel

getDomainValues

public java.lang.String[] getDomainValues(java.lang.String name)

Description copied from interface: IGeneratedModel

Gets domain of given column.

Specified by:

getDomainValues in interface IGeneratedModel

Parameters:

name - column name

Returns:

return domain for given column or null if column is numeric.

getDomainValues

public java.lang.String[] getDomainValues(int i)

Description copied from interface: IGeneratedModel

Returns domain values for i-th column.

Specified by:

getDomainValues in interface IGeneratedModel

Parameters:

i - index of column

Returns:

domain for given enum column or null if columns contains numeric value

mapEnum

public int mapEnum(int colIdx,
          java.lang.String enumValue)

Description copied from interface: IGeneratedModel

Maps given column's enum to integer used by this model. Returns -1 if mapping is not found.

Specified by:

mapEnum in interface IGeneratedModel

getPredsSize

public int getPredsSize()

Description copied from interface: IGeneratedModel

Returns the expected size of preds array which is passed to IGeneratedModel.predict(double[], float[]) function.

Specified by:

getPredsSize in interface IGeneratedModel

Returns:

expected size of preds array

map

public double[] map(java.util.Map<java.lang.String,java.lang.Double> row,
           double[] data)

Takes a HashMap mapping column names to doubles.

Looks up the column names needed by the model, and places the doubles into the data array in the order needed by the model. Missing columns use NaN.

predict

public float[] predict(java.util.Map<java.lang.String,java.lang.Double> row,
              double[] data,
              float[] preds)

predict

public float[] predict(java.util.Map<java.lang.String,java.lang.Double> row,
              float[] preds)

predict

public float[] predict(java.util.Map<java.lang.String,java.lang.Double> row)