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Zheng RuiFeng authored
## What changes were proposed in this pull request? 1, `**Example**` => `**Examples**`, because more algos use `**Examples**`. 2, delete `### Examples` in `Isotonic regression`, because it's not that special in http://spark.apache.org/docs/latest/ml-classification-regression.html 3, add missing marks for `LDA` and other algos. ## How was this patch tested? No tests for it only modify doc Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #15783 from zhengruifeng/doc_fix.
Zheng RuiFeng authored## What changes were proposed in this pull request? 1, `**Example**` => `**Examples**`, because more algos use `**Examples**`. 2, delete `### Examples` in `Isotonic regression`, because it's not that special in http://spark.apache.org/docs/latest/ml-classification-regression.html 3, add missing marks for `LDA` and other algos. ## How was this patch tested? No tests for it only modify doc Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #15783 from zhengruifeng/doc_fix.
ml-clustering.md 6.70 KiB
layout: global
title: Clustering
displayTitle: ClusteringThis page describes clustering algorithms in MLlib. The guide for clustering in the RDD-based API also has relevant information about these algorithms.
Table of Contents
- This will become a table of contents (this text will be scraped). {:toc}
K-means
k-means is one of the most commonly used clustering algorithms that clusters the data points into a predefined number of clusters. The MLlib implementation includes a parallelized variant of the k-means++ method called kmeans||.
KMeans is implemented as an Estimator and generates a KMeansModel as the base model.
Input Columns
| Param name | Type(s) | Default | Description |
|---|---|---|---|
| featuresCol | Vector | "features" | Feature vector |