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

Implements the stochastic variant of the Pegasos (Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et al. (2007). This implementation globally replaces all missing values and transforms nominal attributes into binary ones. It also normalizes all attributes, so the coefficients in the output are based on the normalized data. Can either minimize the hinge loss (SVM) or log loss (logistic regression). For more information, see S. Shalev-Shwartz, Y. Singer, N. Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In: 24th International Conference on MachineLearning, 807-814, 2007.

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

Download SPegasos 1.0.1

Filename	Size
SPegasos-1.0.1.pom
SPegasos-1.0.1.jar	10 KB
SPegasos-1.0.1-tests.jar	4 KB
SPegasos-1.0.1-test-sources.jar	1 KB
SPegasos-1.0.1-sources.jar	6 KB
SPegasos-1.0.1-javadoc.jar	31 KB

Apache Maven

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

Gradle Groovy

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

Gradle Kotlin

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

Apache Buildr

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

Apache Ivy

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

Groovy Grape

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

Scala SBT

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

Leiningen

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