From 41f533825e080b47f2a31f1dc4cbac0adf39e40f Mon Sep 17 00:00:00 2001 From: Lewuathe Date: Sat, 30 Jan 2016 16:23:17 -0800 Subject: [PATCH] [ML][MINOR] Invalid MulticlassClassification reference in ml-guide --- docs/ml-guide.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/ml-guide.md b/docs/ml-guide.md index 5aafd53b584e7..f8279262e673f 100644 --- a/docs/ml-guide.md +++ b/docs/ml-guide.md @@ -627,7 +627,7 @@ Currently, `spark.ml` supports model selection using the [`CrossValidator`](api/ The `Evaluator` can be a [`RegressionEvaluator`](api/scala/index.html#org.apache.spark.ml.evaluation.RegressionEvaluator) for regression problems, a [`BinaryClassificationEvaluator`](api/scala/index.html#org.apache.spark.ml.evaluation.BinaryClassificationEvaluator) -for binary data, or a [`MultiClassClassificationEvaluator`](api/scala/index.html#org.apache.spark.ml.evaluation.MultiClassClassificationEvaluator) +for binary data, or a [`MultiClassClassificationEvaluator`](api/scala/index.html#org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator) for multiclass problems. The default metric used to choose the best `ParamMap` can be overriden by the `setMetricName` method in each of these evaluators.