Modifier and Type | Field and 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 |
Constructor and Description |
---|
RegressionTreeOptions() |
public DataOptions general
@Option(longName="csv-response-split-char", usage="Character to split the CSV response on to generate multiple regression dimensions. Defaults to \':\'.") public char splitChar
@Option(charName=100, longName="max-depth", usage="Maximum depth in the decision tree.") public int depth
@Option(charName=101, longName="split-fraction", usage="Fraction of features in split.") public float fraction
@Option(charName=109, longName="min-child-weight", usage="Minimum child weight.") public float minChildWeight
@Option(charName=112, longName="min-impurity-decrease", usage="Minimumum decrease in impurity required in order for the node to be split.") public float minImpurityDecrease
@Option(charName=114, longName="use-random-split-points", usage="Whether to choose split points for features at random.") public boolean useRandomSplitPoints
@Option(charName=110, longName="normalize", usage="Normalize the leaf outputs so each leaf sums to 1.0.") public boolean normalize
@Option(charName=105, longName="impurity", usage="Impurity measure to use. Defaults to MSE.") public TrainTest.ImpurityType impurityType
@Option(charName=116, longName="tree-type", usage="Tree type.") public TrainTest.TreeType treeType
@Option(longName="print-tree", usage="Prints the decision tree.") public boolean printTree
public String getOptionsDescription()
getOptionsDescription
in interface com.oracle.labs.mlrg.olcut.config.Options
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