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

Implements a least median squared linear regression utilizing the existing weka LinearRegression class to form predictions. Least squared regression functions are generated from random subsamples of the data. The least squared regression with the lowest meadian squared error is chosen as the final model. The basis of the algorithm is Peter J. Rousseeuw, Annick M. Leroy (1987). Robust regression and outlier detection.

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

Download leastMedSquared 1.0.1

Filename	Size
leastMedSquared-1.0.1.pom
leastMedSquared-1.0.1.jar	9 KB
leastMedSquared-1.0.1-tests.jar	4 KB
leastMedSquared-1.0.1-test-sources.jar	1 KB
leastMedSquared-1.0.1-sources.jar	5 KB
leastMedSquared-1.0.1-javadoc.jar	30 KB

Apache Maven

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

Gradle Groovy

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

Gradle Kotlin

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

Apache Buildr

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

Apache Ivy

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

Groovy Grape

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

Scala SBT

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

Leiningen

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