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| -rw-r--r-- | docs/sparkr.md | 41 |
1 files changed, 29 insertions, 12 deletions
diff --git a/docs/sparkr.md b/docs/sparkr.md index d2db78282a..d7ffd9b3f1 100644 --- a/docs/sparkr.md +++ b/docs/sparkr.md @@ -516,18 +516,35 @@ head(teenagers) SparkR supports the following machine learning algorithms currently: -* [`spark.glm`](api/R/spark.glm.html) or [`glm`](api/R/glm.html): [`Generalized Linear Model`](ml-classification-regression.html#generalized-linear-regression) -* [`spark.survreg`](api/R/spark.survreg.html): [`Accelerated Failure Time (AFT) Survival Regression Model`](ml-classification-regression.html#survival-regression) -* [`spark.naiveBayes`](api/R/spark.naiveBayes.html): [`Naive Bayes Model`](ml-classification-regression.html#naive-bayes) -* [`spark.kmeans`](api/R/spark.kmeans.html): [`K-Means Model`](ml-clustering.html#k-means) -* [`spark.logit`](api/R/spark.logit.html): [`Logistic Regression Model`](ml-classification-regression.html#logistic-regression) -* [`spark.isoreg`](api/R/spark.isoreg.html): [`Isotonic Regression Model`](ml-classification-regression.html#isotonic-regression) -* [`spark.gaussianMixture`](api/R/spark.gaussianMixture.html): [`Gaussian Mixture Model`](ml-clustering.html#gaussian-mixture-model-gmm) -* [`spark.lda`](api/R/spark.lda.html): [`Latent Dirichlet Allocation (LDA) Model`](ml-clustering.html#latent-dirichlet-allocation-lda) -* [`spark.mlp`](api/R/spark.mlp.html): [`Multilayer Perceptron Classification Model`](ml-classification-regression.html#multilayer-perceptron-classifier) -* [`spark.gbt`](api/R/spark.gbt.html): `Gradient Boosted Tree Model for` [`Regression`](ml-classification-regression.html#gradient-boosted-tree-regression) `and` [`Classification`](ml-classification-regression.html#gradient-boosted-tree-classifier) -* [`spark.randomForest`](api/R/spark.randomForest.html): `Random Forest Model for` [`Regression`](ml-classification-regression.html#random-forest-regression) `and` [`Classification`](ml-classification-regression.html#random-forest-classifier) -* [`spark.als`](api/R/spark.als.html): [`Alternating Least Squares (ALS) matrix factorization Model`](ml-collaborative-filtering.html#collaborative-filtering) +#### Classification + +* [`spark.logit`](api/R/spark.logit.html): [`Logistic Regression`](ml-classification-regression.html#logistic-regression) +* [`spark.mlp`](api/R/spark.mlp.html): [`Multilayer Perceptron (MLP)`](ml-classification-regression.html#multilayer-perceptron-classifier) +* [`spark.naiveBayes`](api/R/spark.naiveBayes.html): [`Naive Bayes`](ml-classification-regression.html#naive-bayes) + +#### Regression + +* [`spark.survreg`](api/R/spark.survreg.html): [`Accelerated Failure Time (AFT) Survival Model`](ml-classification-regression.html#survival-regression) +* [`spark.glm`](api/R/spark.glm.html) or [`glm`](api/R/glm.html): [`Generalized Linear Model (GLM)`](ml-classification-regression.html#generalized-linear-regression) +* [`spark.isoreg`](api/R/spark.isoreg.html): [`Isotonic Regression`](ml-classification-regression.html#isotonic-regression) + +#### Tree + +* [`spark.gbt`](api/R/spark.gbt.html): `Gradient Boosted Trees for` [`Regression`](ml-classification-regression.html#gradient-boosted-tree-regression) `and` [`Classification`](ml-classification-regression.html#gradient-boosted-tree-classifier) +* [`spark.randomForest`](api/R/spark.randomForest.html): `Random Forest for` [`Regression`](ml-classification-regression.html#random-forest-regression) `and` [`Classification`](ml-classification-regression.html#random-forest-classifier) + +#### Clustering + +* [`spark.gaussianMixture`](api/R/spark.gaussianMixture.html): [`Gaussian Mixture Model (GMM)`](ml-clustering.html#gaussian-mixture-model-gmm) +* [`spark.kmeans`](api/R/spark.kmeans.html): [`K-Means`](ml-clustering.html#k-means) +* [`spark.lda`](api/R/spark.lda.html): [`Latent Dirichlet Allocation (LDA)`](ml-clustering.html#latent-dirichlet-allocation-lda) + +#### Collaborative Filtering + +* [`spark.als`](api/R/spark.als.html): [`Alternating Least Squares (ALS)`](ml-collaborative-filtering.html#collaborative-filtering) + +#### Statistics + * [`spark.kstest`](api/R/spark.kstest.html): `Kolmogorov-Smirnov Test` Under the hood, SparkR uses MLlib to train the model. Please refer to the corresponding section of MLlib user guide for example code. |