nz.ac.waikato.cms.weka:bestFirstTree 1.0.2

Class for building a best-first decision tree classifier. This class uses binary split for both nominal and numeric attributes. For missing values, the method of 'fractional' instances is used. For more information, see: Haijian Shi (2007). Best-first decision tree learning. Hamilton, NZ. Jerome Friedman, Trevor Hastie, Robert Tibshirani (2000). Additive logistic regression : A statistical view of boosting. Annals of statistics. 28(2):337-407.

Categories	Weka Business Logic Libraries Machine Learning
GroupId	nz.ac.waikato.cms.weka
ArtifactId	bestFirstTree
Version	1.0.2
Type	jar

Download bestFirstTree 1.0.2

Filename	Size
bestFirstTree-1.0.2.pom
bestFirstTree-1.0.2.jar	24 KB
bestFirstTree-1.0.2-tests.jar	4 KB
bestFirstTree-1.0.2-test-sources.jar	1 KB
bestFirstTree-1.0.2-sources.jar	16 KB
bestFirstTree-1.0.2-javadoc.jar	31 KB

Apache Maven

<!-- https://jarcasting.com/artifacts/nz.ac.waikato.cms.weka/bestFirstTree/ -->
<dependency>
    <groupId>nz.ac.waikato.cms.weka</groupId>
    <artifactId>bestFirstTree</artifactId>
    <version>1.0.2</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/nz.ac.waikato.cms.weka/bestFirstTree/
implementation 'nz.ac.waikato.cms.weka:bestFirstTree:1.0.2'

Gradle Kotlin

// https://jarcasting.com/artifacts/nz.ac.waikato.cms.weka/bestFirstTree/
implementation ("nz.ac.waikato.cms.weka:bestFirstTree:1.0.2")

Apache Buildr

'nz.ac.waikato.cms.weka:bestFirstTree:jar:1.0.2'

Apache Ivy

<dependency org="nz.ac.waikato.cms.weka" name="bestFirstTree" rev="1.0.2">
  <artifact name="bestFirstTree" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='nz.ac.waikato.cms.weka', module='bestFirstTree', version='1.0.2')
)

Scala SBT

libraryDependencies += "nz.ac.waikato.cms.weka" % "bestFirstTree" % "1.0.2"

Leiningen

[nz.ac.waikato.cms.weka/bestFirstTree "1.0.2"]