Class TrainTest.RegressionTreeOptions

java.lang.Object

org.tribuo.regression.rtree.TrainTest.RegressionTreeOptions

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.config.Options

Enclosing class:

TrainTest

public static class TrainTest.RegressionTreeOptions
extends Object
implements com.oracle.labs.mlrg.olcut.config.Options

Command line options.

Field Summary

Fields

Modifier and Type	Field	Description
int	depth
float	fraction
DataOptions	general
TrainTest.ImpurityType	impurityType
float	minChildWeight
float	minImpurityDecrease
boolean	normalize
boolean	printTree
char	splitChar
TrainTest.TreeType	treeType
boolean	useRandomSplitPoints

Fields inherited from interface com.oracle.labs.mlrg.olcut.config.Options

header

Constructor Summary

Constructors

Constructor	Description
RegressionTreeOptions()

Method Summary

Modifier and Type	Method	Description
String	getOptionsDescription()

Methods inherited from class java.lang.Object

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

Field Details

general

public DataOptions general

splitChar

@Option(longName="csv-response-split-char",
        usage="Character to split the CSV response on to generate multiple regression dimensions. Defaults to ':'.")
public char splitChar

depth

@Option(charName='d',
        longName="max-depth",
        usage="Maximum depth in the decision tree.")
public int depth

fraction

@Option(charName='e',
        longName="split-fraction",
        usage="Fraction of features in split.")
public float fraction

minChildWeight

@Option(charName='m',
        longName="min-child-weight",
        usage="Minimum child weight.")
public float minChildWeight

minImpurityDecrease

@Option(charName='p',
        longName="min-impurity-decrease",
        usage="Minimumum decrease in impurity required in order for the node to be split.")
public float minImpurityDecrease

useRandomSplitPoints

@Option(charName='r',
        longName="use-random-split-points",
        usage="Whether to choose split points for features at random.")
public boolean useRandomSplitPoints

normalize

@Option(charName='n',
        longName="normalize",
        usage="Normalize the leaf outputs so each leaf sums to 1.0.")
public boolean normalize

impurityType

@Option(charName='i',
        longName="impurity",
        usage="Impurity measure to use. Defaults to MSE.")
public TrainTest.ImpurityType impurityType

treeType

@Option(charName='t',
        longName="tree-type",
        usage="Tree type.")
public TrainTest.TreeType treeType

printTree

@Option(longName="print-tree",
        usage="Prints the decision tree.")
public boolean printTree

Constructor Details

RegressionTreeOptions

public RegressionTreeOptions()

Method Details

getOptionsDescription

public String getOptionsDescription()

Specified by:

getOptionsDescription in interface com.oracle.labs.mlrg.olcut.config.Options