Description Usage Arguments Value Note See Also Examples
View source: R/ml_classification.R
ml_naive_bayes
fits a Bernoulli naive Bayes model against a spark_tbl.
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ml_naive_bayes(
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 '-'. |
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 spark_tbl 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. |
... |
additional argument(s) passed to the method. Currently only |
ml_naive_bayes
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 spark_tbl containing predicted labeled in a column named
"prediction".
ml_naive_bayes 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
write_ml
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ## Not run:
data <- as.data.frame(UCBAdmissions)
df <- spark_tbl(data)
# fit a Bernoulli naive Bayes model
model <- ml_naive_bayes(df, Admit ~ Gender + Dept, smoothing = 0)
# get the summary of the model
summary(model)
# make predictions
predictions <- predict(model, df)
# save and load the model
path <- "path/to/model"
write_ml(model, path)
savedModel <- read_ml(path)
summary(savedModel)
## End(Not run)
|
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