l

learning

This module is a custom implementation of the Large Margin Nearest Neighbor classification scheme of Weinberger, Saul, et al. (2009). It contains an implementation of the k-nearest neighbor and LMNN classifier as well as (most importantly) gradient calculation schemes on the LMNN cost function given a sequential data set and a user-choice of alignment algorithm. This enables users to learn parameters of the alignment distance in question using a gradient descent on the LMNN cost function. More information on this approach can be found in the Masters Thesis "Adaptive Affine Sequence Alignment Using Algebraic Dynamic Programming"
http://openresearch.cit-ec.de/projects/tcs
The GNU Affero General Public License, Version 3
Benjamin Paaßen
Files download
File Operation
learning-3.1.1.jar download
learning-3.1.1.pom download
learning-3.1.1-sources.jar download
Apache Maven
<dependency>
  <groupId>de.cit-ec.tcs.alignment</groupId>
  <artifactId>learning</artifactId>
  <version>3.1.1</version>
</dependency>
Gradle Groovy
implementation 'de.cit-ec.tcs.alignment:learning:3.1.1'
Gradle Kotlin
implementation("de.cit-ec.tcs.alignment:learning:3.1.1")
Scala SBT
libraryDependencies += "de.cit-ec.tcs.alignment" % "learning" % "3.1.1"
Groovy Grape
@Grapes(
  @Grab(group='de.cit-ec.tcs.alignment', module='learning', version='3.1.1')
)
Apache Ivy
<dependency org="de.cit-ec.tcs.alignment" name="learning" rev="3.1.1" />
Leiningen
[de.cit-ec.tcs.alignment/learning "3.1.1"]
Apache Buildr
'de.cit-ec.tcs.alignment:learning:jar:3.1.1'