From 0bac3e4cde75678beac02e67b8873fe779e9ad34 Mon Sep 17 00:00:00 2001 From: Zhe Sun Date: Fri, 3 Mar 2017 11:55:57 +0100 Subject: [SPARK-19797][DOC] ML pipeline document correction MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ## What changes were proposed in this pull request? Description about pipeline in this paragraph is incorrect https://spark.apache.org/docs/latest/ml-pipeline.html#how-it-works > If the Pipeline had more **stages**, it would call the LogisticRegressionModel’s transform() method on the DataFrame before passing the DataFrame to the next stage. Reason: Transformer could also be a stage. But only another Estimator will invoke an transform call and pass the data to next stage. The description in the document misleads ML pipeline users. ## How was this patch tested? This is a tiny modification of **docs/ml-pipelines.md**. I jekyll build the modification and check the compiled document. Author: Zhe Sun Closes #17137 from ymwdalex/SPARK-19797-ML-pipeline-document-correction. --- docs/ml-pipeline.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'docs') diff --git a/docs/ml-pipeline.md b/docs/ml-pipeline.md index 7cbb14654e..aa92c0a37c 100644 --- a/docs/ml-pipeline.md +++ b/docs/ml-pipeline.md @@ -132,7 +132,7 @@ The `Pipeline.fit()` method is called on the original `DataFrame`, which has raw The `Tokenizer.transform()` method splits the raw text documents into words, adding a new column with words to the `DataFrame`. The `HashingTF.transform()` method converts the words column into feature vectors, adding a new column with those vectors to the `DataFrame`. Now, since `LogisticRegression` is an `Estimator`, the `Pipeline` first calls `LogisticRegression.fit()` to produce a `LogisticRegressionModel`. -If the `Pipeline` had more stages, it would call the `LogisticRegressionModel`'s `transform()` +If the `Pipeline` had more `Estimator`s, it would call the `LogisticRegressionModel`'s `transform()` method on the `DataFrame` before passing the `DataFrame` to the next stage. A `Pipeline` is an `Estimator`. -- cgit v1.2.3