Repository: spark Updated Branches: refs/heads/master c68fb426d -> 594b14f1e
[SPARK-18793][SPARK-18794][R] add spark.randomForest/spark.gbt to vignettes ## What changes were proposed in this pull request? Mention `spark.randomForest` and `spark.gbt` in vignettes. Keep the content minimal since users can type `?spark.randomForest` to see the full doc. cc: jkbradley Author: Xiangrui Meng <m...@databricks.com> Closes #16264 from mengxr/SPARK-18793. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/594b14f1 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/594b14f1 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/594b14f1 Branch: refs/heads/master Commit: 594b14f1ebd0b3db9f630e504be92228f11b4d9f Parents: c68fb42 Author: Xiangrui Meng <m...@databricks.com> Authored: Tue Dec 13 16:59:09 2016 -0800 Committer: Xiangrui Meng <m...@databricks.com> Committed: Tue Dec 13 16:59:09 2016 -0800 ---------------------------------------------------------------------- R/pkg/vignettes/sparkr-vignettes.Rmd | 32 +++++++++++++++++++++++++++++++ 1 file changed, 32 insertions(+) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/594b14f1/R/pkg/vignettes/sparkr-vignettes.Rmd ---------------------------------------------------------------------- diff --git a/R/pkg/vignettes/sparkr-vignettes.Rmd b/R/pkg/vignettes/sparkr-vignettes.Rmd index 625b759..334daa5 100644 --- a/R/pkg/vignettes/sparkr-vignettes.Rmd +++ b/R/pkg/vignettes/sparkr-vignettes.Rmd @@ -449,6 +449,10 @@ SparkR supports the following machine learning models and algorithms. * Generalized Linear Model (GLM) +* Random Forest + +* Gradient-Boosted Trees (GBT) + * Naive Bayes Model * $k$-means Clustering @@ -526,6 +530,34 @@ gaussianFitted <- predict(gaussianGLM, carsDF) head(select(gaussianFitted, "model", "prediction", "mpg", "wt", "hp")) ``` +#### Random Forest + +`spark.randomForest` fits a [random forest](https://en.wikipedia.org/wiki/Random_forest) classification or regression model on a `SparkDataFrame`. +Users can call `summary` to get a summary of the fitted model, `predict` to make predictions, and `write.ml`/`read.ml` to save/load fitted models. + +In the following example, we use the `longley` dataset to train a random forest and make predictions: + +```{r, warning=FALSE} +df <- createDataFrame(longley) +rfModel <- spark.randomForest(df, Employed ~ ., type = "regression", maxDepth = 2, numTrees = 2) +summary(rfModel) +predictions <- predict(rfModel, df) +``` + +#### Gradient-Boosted Trees + +`spark.gbt` fits a [gradient-boosted tree](https://en.wikipedia.org/wiki/Gradient_boosting) classification or regression model on a `SparkDataFrame`. +Users can call `summary` to get a summary of the fitted model, `predict` to make predictions, and `write.ml`/`read.ml` to save/load fitted models. + +Similar to the random forest example above, we use the `longley` dataset to train a gradient-boosted tree and make predictions: + +```{r, warning=FALSE} +df <- createDataFrame(longley) +gbtModel <- spark.gbt(df, Employed ~ ., type = "regression", maxDepth = 2, maxIter = 2) +summary(gbtModel) +predictions <- predict(gbtModel, df) +``` + #### Naive Bayes Model Naive Bayes model assumes independence among the features. `spark.naiveBayes` fits a [Bernoulli naive Bayes model](https://en.wikipedia.org/wiki/Naive_Bayes_classifier#Bernoulli_naive_Bayes) against a SparkDataFrame. The data should be all categorical. These models are often used for document classification. --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
