Spark library for generalized K-Means clustering. Supports general Bregman divergences. Suitable for clustering probabilistic data, time series data, high dimensional data, and very large data.
- spark-mllib
- itakura-saito-divergence
- k-means
- bregman-divergence
- cosine-similarity
- euclidean-distance
- clustering
- similarity-search
- spark
- entropy
- embeddings
- kullback-leibler-divergence
Scala versions:
2.10
massivedatascience-clusterer 1.0.2
Group ID:
derrickburns
Artifact ID:
massivedatascience-clusterer_2.10
Version:
1.0.2
Release Date:
Mar 5, 2015
Licenses:
libraryDependencies += "derrickburns" %% "massivedatascience-clusterer" % "1.0.2"
resolvers += Resolver.bintrayRepo("derrickburns", "maven")
ivy"derrickburns::massivedatascience-clusterer:1.0.2"
MavenRepository("https://dl.bintray.com/derrickburns/maven")
//> using dep "derrickburns::massivedatascience-clusterer:1.0.2"
import $ivy.`derrickburns::massivedatascience-clusterer:1.0.2` import ammonite._, Resolvers._ val res = Resolver.Http( "Bintray derrickburns maven", "Some(https://dl.bintray.com/derrickburns/maven)", IvyPattern, false) interp.resolvers() = interp.resolvers() :+ res
<dependency> <groupId>derrickburns</groupId> <artifactId>massivedatascience-clusterer_2.10</artifactId> <version>1.0.2</version> </dependency>
compile group: 'derrickburns', name: 'massivedatascience-clusterer_2.10', version: '1.0.2'
