| Class | Description |
|---|---|
| BisectingKMeans |
A bisecting k-means algorithm based on the paper "A comparison of document clustering techniques"
by Steinbach, Karypis, and Kumar, with modification to fit Spark.
|
| BisectingKMeansModel |
Model fitted by BisectingKMeans.
|
| BisectingKMeansSummary |
:: Experimental ::
Summary of BisectingKMeans.
|
| ClusteringSummary |
:: Experimental ::
Summary of clustering algorithms.
|
| DistributedLDAModel |
Distributed model fitted by
LDA. |
| ExpectationAggregator |
ExpectationAggregator computes the partial expectation results.
|
| GaussianMixture |
Gaussian Mixture clustering.
|
| GaussianMixtureModel |
Multivariate Gaussian Mixture Model (GMM) consisting of k Gaussians, where points
are drawn from each Gaussian i with probability weights(i).
|
| GaussianMixtureSummary |
:: Experimental ::
Summary of GaussianMixture.
|
| KMeans |
K-means clustering with support for k-means|| initialization proposed by Bahmani et al.
|
| KMeansModel |
Model fitted by KMeans.
|
| KMeansSummary |
:: Experimental ::
Summary of KMeans.
|
| LDA |
Latent Dirichlet Allocation (LDA), a topic model designed for text documents.
|
| LDAModel |
Model fitted by
LDA. |
| LocalLDAModel |
Local (non-distributed) model fitted by
LDA. |