MVN

nz.ac.waikato.cms.weka : multiLayerPerceptrons

Maven & Gradle

Oct 31, 2016

multiLayerPerceptrons · This package currently contains classes for training multilayer perceptrons with one hidden layer, where the number of hidden units is user specified. MLPClassifier can be used for classification problems and MLPRegressor is the corresponding class for numeric prediction tasks. The former has as many output units as there are classes, the latter only one output unit. Both minimise a penalised squared error with a quadratic penalty on the (non-bias) weights, i.e., they implement "weight decay", where this penalised error is averaged over all training instances. The size of the penalty can be determined by the user by modifying the "ridge" parameter to control overfitting. The sum of squared weights is multiplied by this parameter before added to the squared error. Both classes use BFGS optimisation by default to find parameters that correspond to a local minimum of the error function. but optionally conjugated gradient descent is available, which can be faster for problems with many parameters. Logistic functions are used as the activation functions for all units apart from the output unit in MLPRegressor, which employs the identity function. Input attributes are standardised to zero mean and unit variance. MLPRegressor also rescales the target attribute (i.e., "class") using standardisation. All network parameters are initialised with small normally distributed random values.

<dependency>
    <groupId>nz.ac.waikato.cms.weka</groupId>
    <artifactId>multiLayerPerceptrons</artifactId>
    <version>1.0.10</version>
</dependency>
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pom.xml
Table Of Contents

Latest Version

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

  • Latest Stable: 1.0.10

All Versions

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

Version Vulnerabilities Updated
1.0.x
multiLayerPerceptrons-1.0.10
multiLayerPerceptrons-1.0.9
multiLayerPerceptrons-1.0.8
multiLayerPerceptrons-1.0.7
multiLayerPerceptrons-1.0.5
multiLayerPerceptrons-1.0.4
multiLayerPerceptrons-1.0.3
multiLayerPerceptrons-1.0.2
multiLayerPerceptrons-1.0.1
multiLayerPerceptrons-1.0.0

How to add a dependency to Maven

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

<dependency>
    <groupId>nz.ac.waikato.cms.weka</groupId>
    <artifactId>multiLayerPerceptrons</artifactId>
    <version>1.0.10</version>
</dependency>

How to add a dependency to Gradle

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

implementation 'nz.ac.waikato.cms.weka:multiLayerPerceptrons:1.0.10'

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

implementation("nz.ac.waikato.cms.weka:multiLayerPerceptrons:1.0.10")

How to add a dependency to SBT Scala

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

libraryDependencies += "nz.ac.waikato.cms.weka" % "multiLayerPerceptrons" % "1.0.10"

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