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| <table width="100%" summary="page for spark.gaussianMixture {SparkR}"><tr><td>spark.gaussianMixture {SparkR}</td><td style="text-align: right;">R Documentation</td></tr></table> |
| |
| <h2>Multivariate Gaussian Mixture Model (GMM)</h2> |
| |
| <h3>Description</h3> |
| |
| <p>Fits multivariate gaussian mixture model against a SparkDataFrame, similarly to R's |
| mvnormalmixEM(). Users can call <code>summary</code> to print a summary of the fitted model, |
| <code>predict</code> to make predictions on new data, and <code>write.ml</code>/<code>read.ml</code> |
| to save/load fitted models. |
| </p> |
| |
| |
| <h3>Usage</h3> |
| |
| <pre> |
| spark.gaussianMixture(data, formula, ...) |
| |
| ## S4 method for signature 'SparkDataFrame,formula' |
| spark.gaussianMixture(data, formula, k = 2, maxIter = 100, tol = 0.01) |
| |
| ## S4 method for signature 'GaussianMixtureModel' |
| summary(object) |
| |
| ## S4 method for signature 'GaussianMixtureModel' |
| predict(object, newData) |
| |
| ## S4 method for signature 'GaussianMixtureModel,character' |
| write.ml(object, path, overwrite = FALSE) |
| </pre> |
| |
| |
| <h3>Arguments</h3> |
| |
| <table summary="R argblock"> |
| <tr valign="top"><td><code>data</code></td> |
| <td> |
| <p>a SparkDataFrame for training.</p> |
| </td></tr> |
| <tr valign="top"><td><code>formula</code></td> |
| <td> |
| <p>a symbolic description of the model to be fitted. Currently only a few formula |
| operators are supported, including '~', '.', ':', '+', and '-'. |
| Note that the response variable of formula is empty in spark.gaussianMixture.</p> |
| </td></tr> |
| <tr valign="top"><td><code>...</code></td> |
| <td> |
| <p>additional arguments passed to the method.</p> |
| </td></tr> |
| <tr valign="top"><td><code>k</code></td> |
| <td> |
| <p>number of independent Gaussians in the mixture model.</p> |
| </td></tr> |
| <tr valign="top"><td><code>maxIter</code></td> |
| <td> |
| <p>maximum iteration number.</p> |
| </td></tr> |
| <tr valign="top"><td><code>tol</code></td> |
| <td> |
| <p>the convergence tolerance.</p> |
| </td></tr> |
| <tr valign="top"><td><code>object</code></td> |
| <td> |
| <p>a fitted gaussian mixture model.</p> |
| </td></tr> |
| <tr valign="top"><td><code>newData</code></td> |
| <td> |
| <p>a SparkDataFrame for testing.</p> |
| </td></tr> |
| <tr valign="top"><td><code>path</code></td> |
| <td> |
| <p>the directory where the model is saved.</p> |
| </td></tr> |
| <tr valign="top"><td><code>overwrite</code></td> |
| <td> |
| <p>overwrites or not if the output path already exists. Default is FALSE |
| which means throw exception if the output path exists.</p> |
| </td></tr> |
| </table> |
| |
| |
| <h3>Value</h3> |
| |
| <p><code>spark.gaussianMixture</code> returns a fitted multivariate gaussian mixture model. |
| </p> |
| <p><code>summary</code> returns summary of the fitted model, which is a list. |
| The list includes the model's <code>lambda</code> (lambda), <code>mu</code> (mu), |
| <code>sigma</code> (sigma), <code>loglik</code> (loglik), and <code>posterior</code> (posterior). |
| </p> |
| <p><code>predict</code> returns a SparkDataFrame containing predicted labels in a column named |
| "prediction". |
| </p> |
| |
| |
| <h3>Note</h3> |
| |
| <p>spark.gaussianMixture since 2.1.0 |
| </p> |
| <p>summary(GaussianMixtureModel) since 2.1.0 |
| </p> |
| <p>predict(GaussianMixtureModel) since 2.1.0 |
| </p> |
| <p>write.ml(GaussianMixtureModel, character) since 2.1.0 |
| </p> |
| |
| |
| <h3>See Also</h3> |
| |
| <p>mixtools: <a href="https://cran.r-project.org/package=mixtools">https://cran.r-project.org/package=mixtools</a> |
| </p> |
| <p><a href="predict.html">predict</a>, <a href="read.ml.html">read.ml</a>, <a href="write.ml.html">write.ml</a> |
| </p> |
| |
| |
| <h3>Examples</h3> |
| |
| <pre><code class="r">## Not run: |
| ##D sparkR.session() |
| ##D library(mvtnorm) |
| ##D set.seed(100) |
| ##D a <- rmvnorm(4, c(0, 0)) |
| ##D b <- rmvnorm(6, c(3, 4)) |
| ##D data <- rbind(a, b) |
| ##D df <- createDataFrame(as.data.frame(data)) |
| ##D model <- spark.gaussianMixture(df, ~ V1 + V2, k = 2) |
| ##D summary(model) |
| ##D |
| ##D # fitted values on training data |
| ##D fitted <- predict(model, df) |
| ##D head(select(fitted, "V1", "prediction")) |
| ##D |
| ##D # save fitted model to input path |
| ##D path <- "path/to/model" |
| ##D write.ml(model, path) |
| ##D |
| ##D # can also read back the saved model and print |
| ##D savedModel <- read.ml(path) |
| ##D summary(savedModel) |
| ## End(Not run) |
| </code></pre> |
| |
| |
| <hr /><div style="text-align: center;">[Package <em>SparkR</em> version 2.4.7 <a href="00Index.html">Index</a>]</div> |
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