Adaptive Kmeans algorithm based on threshold
Released May 9, 2014 by Jungsuk Kwac
Adaptive K-means algorithm with various threshold settings. It support two distance metric: Euclidean distance, Cosine distance (1 - cosine similarity) In version 1.1, it contains one more threshold condition.
This package can be included as a dependency from a Java or Scala project by including
the following your project's
about embedding Renjin in JVM-based projects.
<dependencies> <dependency> <groupId>org.renjin.cran</groupId> <artifactId>akmeans</artifactId> <version>1.1-b240</version> </dependency> </dependencies> <repositories> <repository> <id>bedatadriven</id> <name>bedatadriven public repo</name> <url>https://nexus.bedatadriven.com/content/groups/public/</url> </repository> </repositories>
If you're using Renjin from the command line, you load this library by invoking:
This package was last tested against Renjin 0.9.2622 on Apr 7, 2018.