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

Class implementing a HyperPipe classifier. For each category a HyperPipe is constructed that contains all points of that category (essentially records the attribute bounds observed for each category). Test instances are classified according to the category that "most contains the instance". Does not handle numeric class, or missing values in test cases. Extremely simple algorithm, but has the advantage of being extremely fast, and works quite well when you have "smegloads" of attributes.

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

Download hyperPipes 1.0.1

Filename	Size
hyperPipes-1.0.1.pom
hyperPipes-1.0.1.jar	8 KB
hyperPipes-1.0.1-tests.jar	4 KB
hyperPipes-1.0.1-test-sources.jar	1 KB
hyperPipes-1.0.1-sources.jar	4 KB
hyperPipes-1.0.1-javadoc.jar	24 KB

Apache Maven

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

Gradle Groovy

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

Gradle Kotlin

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

Apache Buildr

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

Apache Ivy

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

Groovy Grape

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

Scala SBT

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

Leiningen

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