kernelLogisticRegression

This package contains a classifier that can be used to train a two-class kernel logistic regression model with the kernel functions that are available in WEKA. It optimises the negative log-likelihood with a quadratic penalty. Both, BFGS and conjugate gradient descent, are available as optimisation methods, but the former is normally faster. It is possible to use multiple threads, but the speed-up is generally very marginal when used with BFGS optimisation. With conjugate gradient descent optimisation, greater speed-ups can be achieved when using multiple threads. With the default kernel, the dot product kernel, this method produces results that are close to identical to those obtained using standard logistic regression in WEKA, provided a sufficiently large value for the parameter determining the size of the quadratic penalty is used in both cases.

License

License

Categories

Categories

Weka Business Logic Libraries Machine Learning
GroupId

GroupId

nz.ac.waikato.cms.weka
ArtifactId

ArtifactId

kernelLogisticRegression
Last Version

Last Version

1.0.0
Release Date

Release Date

Type

Type

jar
Description

Description

kernelLogisticRegression
This package contains a classifier that can be used to train a two-class kernel logistic regression model with the kernel functions that are available in WEKA. It optimises the negative log-likelihood with a quadratic penalty. Both, BFGS and conjugate gradient descent, are available as optimisation methods, but the former is normally faster. It is possible to use multiple threads, but the speed-up is generally very marginal when used with BFGS optimisation. With conjugate gradient descent optimisation, greater speed-ups can be achieved when using multiple threads. With the default kernel, the dot product kernel, this method produces results that are close to identical to those obtained using standard logistic regression in WEKA, provided a sufficiently large value for the parameter determining the size of the quadratic penalty is used in both cases.
Project URL

Project URL

http://weka.sourceforge.net/doc.packages/kernelLogisticRegression
Project Organization

Project Organization

University of Waikato, Hamilton, NZ
Source Code Management

Source Code Management

https://svn.cms.waikato.ac.nz/svn/weka/tags/kernelLogisticRegression-1.0.0

Download kernelLogisticRegression

How to add to project

<!-- https://jarcasting.com/artifacts/nz.ac.waikato.cms.weka/kernelLogisticRegression/ -->
<dependency>
    <groupId>nz.ac.waikato.cms.weka</groupId>
    <artifactId>kernelLogisticRegression</artifactId>
    <version>1.0.0</version>
</dependency>
// https://jarcasting.com/artifacts/nz.ac.waikato.cms.weka/kernelLogisticRegression/
implementation 'nz.ac.waikato.cms.weka:kernelLogisticRegression:1.0.0'
// https://jarcasting.com/artifacts/nz.ac.waikato.cms.weka/kernelLogisticRegression/
implementation ("nz.ac.waikato.cms.weka:kernelLogisticRegression:1.0.0")
'nz.ac.waikato.cms.weka:kernelLogisticRegression:jar:1.0.0'
<dependency org="nz.ac.waikato.cms.weka" name="kernelLogisticRegression" rev="1.0.0">
  <artifact name="kernelLogisticRegression" type="jar" />
</dependency>
@Grapes(
@Grab(group='nz.ac.waikato.cms.weka', module='kernelLogisticRegression', version='1.0.0')
)
libraryDependencies += "nz.ac.waikato.cms.weka" % "kernelLogisticRegression" % "1.0.0"
[nz.ac.waikato.cms.weka/kernelLogisticRegression "1.0.0"]

Dependencies

compile (1)

Group / Artifact Type Version
nz.ac.waikato.cms.weka : weka-dev jar [3.7.6,)

test (2)

Group / Artifact Type Version
nz.ac.waikato.cms.weka : weka-dev test-jar [3.7.6,)
junit : junit jar 3.8.2

Project Modules

There are no modules declared in this project.

Versions

Version
1.0.0