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| author | Xusen Yin <yinxusen@gmail.com> | 2016-03-22 14:16:51 -0700 |
|---|---|---|
| committer | Xiangrui Meng <meng@databricks.com> | 2016-03-22 14:16:51 -0700 |
| commit | d6dc12ef0146ae409834c78737c116050961f350 (patch) | |
| tree | 7e99255f2a15ee2d088677253465ec6951b0a8d4 /R/DOCUMENTATION.md | |
| parent | b2b1ad7d4cc3b3469c3d2c841b40b58ed0e34447 (diff) | |
| download | spark-d6dc12ef0146ae409834c78737c116050961f350.tar.gz spark-d6dc12ef0146ae409834c78737c116050961f350.tar.bz2 spark-d6dc12ef0146ae409834c78737c116050961f350.zip | |
[SPARK-13449] Naive Bayes wrapper in SparkR
## 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
Author: Xusen Yin <yinxusen@gmail.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes #11890 from mengxr/SPARK-13449.
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