nz.ac.waikato.cms.weka:extraTrees 1.0.1

Package for generating a single Extra-Tree. Use with the RandomCommittee meta classifier to generate an Extra-Trees forest for classification or regression. This classifier requires all predictors to be numeric. Missing values are not allowed. Instance weights are taken into account. For more information, see Pierre Geurts, Damien Ernst, Louis Wehenkel (2006). Extremely randomized trees. Machine Learning. 63(1):3-42.

Categories	Weka Business Logic Libraries Machine Learning
GroupId	nz.ac.waikato.cms.weka
ArtifactId	extraTrees
Version	1.0.1
Type	jar

Download extraTrees 1.0.1

Filename	Size
extraTrees-1.0.1.pom
extraTrees-1.0.1.jar	11 KB
extraTrees-1.0.1-tests.jar	4 KB
extraTrees-1.0.1-test-sources.jar	1 KB
extraTrees-1.0.1-sources.jar	6 KB
extraTrees-1.0.1-javadoc.jar	42 KB

Apache Maven

<!-- https://jarcasting.com/artifacts/nz.ac.waikato.cms.weka/extraTrees/ -->
<dependency>
    <groupId>nz.ac.waikato.cms.weka</groupId>
    <artifactId>extraTrees</artifactId>
    <version>1.0.1</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/nz.ac.waikato.cms.weka/extraTrees/
implementation 'nz.ac.waikato.cms.weka:extraTrees:1.0.1'

Gradle Kotlin

// https://jarcasting.com/artifacts/nz.ac.waikato.cms.weka/extraTrees/
implementation ("nz.ac.waikato.cms.weka:extraTrees:1.0.1")

Apache Buildr

'nz.ac.waikato.cms.weka:extraTrees:jar:1.0.1'

Apache Ivy

<dependency org="nz.ac.waikato.cms.weka" name="extraTrees" rev="1.0.1">
  <artifact name="extraTrees" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='nz.ac.waikato.cms.weka', module='extraTrees', version='1.0.1')
)

Scala SBT

libraryDependencies += "nz.ac.waikato.cms.weka" % "extraTrees" % "1.0.1"

Leiningen

[nz.ac.waikato.cms.weka/extraTrees "1.0.1"]