MVN

nz.ac.waikato.cms.weka : iterativeAbsoluteErrorRegression

Maven & Gradle

Jan 25, 2016

iterativeAbsoluteErrorRegression · Provides a regression scheme that uses Schlossmacher's iteratively reweighted least squares method to fit a model that minimizes absolute error. The scheme can be used with any base learner in WEKA that performs least-squares regression

<dependency>
    <groupId>nz.ac.waikato.cms.weka</groupId>
    <artifactId>iterativeAbsoluteErrorRegression</artifactId>
    <version>1.0.0</version>
</dependency>
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pom.xml
Table Of Contents

Latest Version

Choose a version of nz.ac.waikato.cms.weka : iterativeAbsoluteErrorRegression to add to Maven or Gradle - Latest Versions:

  • Latest Stable: 1.0.0

All Versions

Choose a version of nz.ac.waikato.cms.weka : iterativeAbsoluteErrorRegression to add to Maven or Gradle - All Versions:

Version Vulnerabilities Updated
1.0.x
iterativeAbsoluteErrorRegression-1.0.0

How to add a dependency to Maven

Add the following nz.ac.waikato.cms.weka : iterativeAbsoluteErrorRegression maven dependency to the pom.xml file with your favorite IDE (IntelliJ / Eclipse / Netbeans):

<dependency>
    <groupId>nz.ac.waikato.cms.weka</groupId>
    <artifactId>iterativeAbsoluteErrorRegression</artifactId>
    <version>1.0.0</version>
</dependency>

How to add a dependency to Gradle

Gradle Groovy DSL: Add the following nz.ac.waikato.cms.weka : iterativeAbsoluteErrorRegression gradle dependency to your build.gradle file:

implementation 'nz.ac.waikato.cms.weka:iterativeAbsoluteErrorRegression:1.0.0'

Gradle Kotlin DSL: Add the following nz.ac.waikato.cms.weka : iterativeAbsoluteErrorRegression gradle kotlin dependency to your build.gradle.kts file:

implementation("nz.ac.waikato.cms.weka:iterativeAbsoluteErrorRegression:1.0.0")

How to add a dependency to SBT Scala

SBT Scala: Add the following nz.ac.waikato.cms.weka : iterativeAbsoluteErrorRegression sbt scala dependency to your build.sbt file:

libraryDependencies += "nz.ac.waikato.cms.weka" % "iterativeAbsoluteErrorRegression" % "1.0.0"

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