spark.naiveBayes {SparkR} | R Documentation |

`spark.naiveBayes`

fits a Bernoulli naive Bayes model against a SparkDataFrame.
Users can call `summary`

to print a summary of the fitted model, `predict`

to make
predictions on new data, and `write.ml`

/`read.ml`

to save/load fitted models.
Only categorical data is supported.

spark.naiveBayes(data, formula, ...) ## S4 method for signature 'SparkDataFrame,formula' spark.naiveBayes( data, formula, smoothing = 1, handleInvalid = c("error", "keep", "skip") ) ## S4 method for signature 'NaiveBayesModel' summary(object) ## S4 method for signature 'NaiveBayesModel' predict(object, newData) ## S4 method for signature 'NaiveBayesModel,character' write.ml(object, path, overwrite = FALSE)

`data` |
a |

`formula` |
a symbolic description of the model to be fitted. Currently only a few formula operators are supported, including '~', '.', ':', '+', and '-'. |

`...` |
additional argument(s) passed to the method. Currently only |

`smoothing` |
smoothing parameter. |

`handleInvalid` |
How to handle invalid data (unseen labels or NULL values) in features and label column of string type. Supported options: "skip" (filter out rows with invalid data), "error" (throw an error), "keep" (put invalid data in a special additional bucket, at index numLabels). Default is "error". |

`object` |
a naive Bayes model fitted by |

`newData` |
a SparkDataFrame for testing. |

`path` |
the directory where the model is saved. |

`overwrite` |
overwrites or not if the output path already exists. Default is FALSE which means throw exception if the output path exists. |

`spark.naiveBayes`

returns a fitted naive Bayes model.

`summary`

returns summary information of the fitted model, which is a list.
The list includes `apriori`

(the label distribution) and
`tables`

(conditional probabilities given the target label).

`predict`

returns a SparkDataFrame containing predicted labeled in a column named
"prediction".

spark.naiveBayes since 2.0.0

summary(NaiveBayesModel) since 2.0.0

predict(NaiveBayesModel) since 2.0.0

write.ml(NaiveBayesModel, character) since 2.0.0

e1071: https://cran.r-project.org/package=e1071

```
## 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)
```

[Package *SparkR* version 3.1.2 Index]