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

Interactively classify through visual means. You are Presented with a scatter graph of the data against two user selectable attributes, as well as a view of the decision tree. You can create binary splits by creating polygons around data plotted on the scatter graph, as well as by allowing another classifier to take over at points in the decision tree should you see fit. For more information see: Malcolm Ware, Eibe Frank, Geoffrey Holmes, Mark Hall, Ian H. Witten (2001). Interactive machine learning: letting users build classifiers. Int. J. Hum.-Comput. Stud. 55(3):281-292.

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

Download userClassifier 1.0.1

Filename	Size
userClassifier-1.0.1.pom
userClassifier-1.0.1.jar	19 KB
userClassifier-1.0.1-tests.jar	4 KB
userClassifier-1.0.1-test-sources.jar	1 KB
userClassifier-1.0.1-sources.jar	11 KB
userClassifier-1.0.1-javadoc.jar	27 KB

Apache Maven

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

Gradle Groovy

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

Gradle Kotlin

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

Apache Buildr

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

Apache Ivy

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

Groovy Grape

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

Scala SBT

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

Leiningen

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