[SPARK-13449] Naive Bayes wrapper in SparkR

[mengxr]

What changes were proposed in this pull request?

This PR continues the work in #11486 from @yinxusen with some code refactoring. In R package e1071, naiveBayes supports both categorical (Bernoulli) and continuous features (Gaussian), while in MLlib we support Bernoulli and multinomial. This PR implements the common subset: Bernoulli.

I moved the implementation out from SparkRWrappers to NaiveBayesWrapper to make it easier to read. Argument names, default values, and summary now match e1071's naiveBayes.

I removed the preprocess part that omit NA values because we don't know which columns to process.

How was this patch tested?

Test against output from R package e1071's naiveBayes.

cc: @yanboliang @yinxusen

Closes #11486

[SparkQA]

Test build #53781 has finished for PR 11890 at commit 43e6fa5.

• This patch fails some tests.
• This patch merges cleanly.
• This patch adds no public classes.

[SparkQA]

Test build #53782 has finished for PR 11890 at commit b3312c7.

• This patch fails some tests.
• This patch merges cleanly.
• This patch adds no public classes.

[SparkQA]

Test build #53783 has finished for PR 11890 at commit 12a41bb.

• This patch fails R style tests.
• This patch merges cleanly.
• This patch adds no public classes.

[SparkQA]

Test build #53787 has finished for PR 11890 at commit 0ac224e.

• This patch passes all tests.
• This patch merges cleanly.
• This patch adds no public classes.

[thunterdb]

@mengxr it looks great, I have no comment

[mengxr]

Thanks! Merged into master.