-
Timothy Hunter authored
[SPARK-12212][ML][DOC] Clarifies the difference between spark.ml, spark.mllib and mllib in the documentation. Replaces a number of occurences of `MLlib` in the documentation that were meant to refer to the `spark.mllib` package instead. It should clarify for new users the difference between `spark.mllib` (the package) and MLlib (the umbrella project for ML in spark). It also removes some files that I forgot to delete with #10207 Author: Timothy Hunter <timhunter@databricks.com> Closes #10234 from thunterdb/12212.
Timothy Hunter authored[SPARK-12212][ML][DOC] Clarifies the difference between spark.ml, spark.mllib and mllib in the documentation. Replaces a number of occurences of `MLlib` in the documentation that were meant to refer to the `spark.mllib` package instead. It should clarify for new users the difference between `spark.mllib` (the package) and MLlib (the umbrella project for ML in spark). It also removes some files that I forgot to delete with #10207 Author: Timothy Hunter <timhunter@databricks.com> Closes #10234 from thunterdb/12212.
ml-clustering.md 1.03 KiB
layout: global
title: Clustering - spark.ml
displayTitle: Clustering - spark.mlIn this section, we introduce the pipeline API for clustering in mllib.
Table of Contents
- This will become a table of contents (this text will be scraped). {:toc}
Latent Dirichlet allocation (LDA)
LDA is implemented as an Estimator that supports both EMLDAOptimizer and OnlineLDAOptimizer,
and generates a LDAModel as the base models. Expert users may cast a LDAModel generated by
EMLDAOptimizer to a DistributedLDAModel if needed.
Refer to the Scala API docs for more details.
{% include_example scala/org/apache/spark/examples/ml/LDAExample.scala %}
Refer to the Java API docs for more details.
{% include_example java/org/apache/spark/examples/ml/JavaLDAExample.java %}