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| <table width="100%" summary="page for spark.naiveBayes {SparkR}"><tr><td>spark.naiveBayes {SparkR}</td><td align="right">R Documentation</td></tr></table> |
| |
| <h2>Naive Bayes Models</h2> |
| |
| <h3>Description</h3> |
| |
| <p><code>spark.naiveBayes</code> fits a Bernoulli naive Bayes model against a SparkDataFrame. |
| 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. |
| Only categorical data is supported. |
| </p> |
| |
| |
| <h3>Usage</h3> |
| |
| <pre> |
| spark.naiveBayes(data, formula, ...) |
| |
| ## S4 method for signature 'NaiveBayesModel' |
| predict(object, newData) |
| |
| ## S4 method for signature 'NaiveBayesModel' |
| summary(object) |
| |
| ## S4 method for signature 'SparkDataFrame,formula' |
| spark.naiveBayes(data, formula, |
| smoothing = 1) |
| |
| ## S4 method for signature 'NaiveBayesModel,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 <code>SparkDataFrame</code> of observations and labels for model fitting.</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 '-'.</p> |
| </td></tr> |
| <tr valign="top"><td><code>...</code></td> |
| <td> |
| <p>additional argument(s) passed to the method. Currently only <code>smoothing</code>.</p> |
| </td></tr> |
| <tr valign="top"><td><code>object</code></td> |
| <td> |
| <p>a naive Bayes model fitted by <code>spark.naiveBayes</code>.</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>smoothing</code></td> |
| <td> |
| <p>smoothing parameter.</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>predict</code> returns a SparkDataFrame containing predicted labeled in a column named |
| "prediction". |
| </p> |
| <p><code>summary</code> returns summary information of the fitted model, which is a list. |
| The list includes <code>apriori</code> (the label distribution) and |
| <code>tables</code> (conditional probabilities given the target label). |
| </p> |
| <p><code>spark.naiveBayes</code> returns a fitted naive Bayes model. |
| </p> |
| |
| |
| <h3>Note</h3> |
| |
| <p>predict(NaiveBayesModel) since 2.0.0 |
| </p> |
| <p>summary(NaiveBayesModel) since 2.0.0 |
| </p> |
| <p>spark.naiveBayes since 2.0.0 |
| </p> |
| <p>write.ml(NaiveBayesModel, character) since 2.0.0 |
| </p> |
| |
| |
| <h3>See Also</h3> |
| |
| <p>e1071: <a href="https://cran.r-project.org/package=e1071">https://cran.r-project.org/package=e1071</a> |
| </p> |
| <p><a href="write.ml.html">write.ml</a> |
| </p> |
| |
| |
| <h3>Examples</h3> |
| |
| <pre><code class="r">## Not run: |
| ##D data <- as.data.frame(UCBAdmissions) |
| ##D df <- createDataFrame(data) |
| ##D |
| ##D # fit a Bernoulli naive Bayes model |
| ##D model <- spark.naiveBayes(df, Admit ~ Gender + Dept, smoothing = 0) |
| ##D |
| ##D # get the summary of the model |
| ##D summary(model) |
| ##D |
| ##D # make predictions |
| ##D predictions <- predict(model, df) |
| ##D |
| ##D # save and load the model |
| ##D path <- "path/to/model" |
| ##D write.ml(model, path) |
| ##D savedModel <- read.ml(path) |
| ##D summary(savedModel) |
| ## End(Not run) |
| </code></pre> |
| |
| |
| <hr><div align="center">[Package <em>SparkR</em> version 2.1.1 <a href="00Index.html">Index</a>]</div> |
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