From 01f09b161217193b797c8c85969d17054c958615 Mon Sep 17 00:00:00 2001 From: "Joseph K. Bradley" Date: Wed, 13 Jul 2016 12:33:39 -0700 Subject: [SPARK-14812][ML][MLLIB][PYTHON] Experimental, DeveloperApi annotation audit for ML ## What changes were proposed in this pull request? General decisions to follow, except where noted: * spark.mllib, pyspark.mllib: Remove all Experimental annotations. Leave DeveloperApi annotations alone. * spark.ml, pyspark.ml ** Annotate Estimator-Model pairs of classes and companion objects the same way. ** For all algorithms marked Experimental with Since tag <= 1.6, remove Experimental annotation. ** For all algorithms marked Experimental with Since tag = 2.0, leave Experimental annotation. * DeveloperApi annotations are left alone, except where noted. * No changes to which types are sealed. Exceptions where I am leaving items Experimental in spark.ml, pyspark.ml, mainly because the items are new: * Model Summary classes * MLWriter, MLReader, MLWritable, MLReadable * Evaluator and subclasses: There is discussion of changes around evaluating multiple metrics at once for efficiency. * RFormula: Its behavior may need to change slightly to match R in edge cases. * AFTSurvivalRegression * MultilayerPerceptronClassifier DeveloperApi changes: * ml.tree.Node, ml.tree.Split, and subclasses should no longer be DeveloperApi ## How was this patch tested? N/A Note to reviewers: * spark.ml.clustering.LDA underwent significant changes (additional methods), so let me know if you want me to leave it Experimental. * Be careful to check for cases where a class should no longer be Experimental but has an Experimental method, val, or other feature. I did not find such cases, but please verify. Author: Joseph K. Bradley Closes #14147 from jkbradley/experimental-audit. --- python/pyspark/ml/tuning.py | 6 ------ 1 file changed, 6 deletions(-) (limited to 'python/pyspark/ml/tuning.py') diff --git a/python/pyspark/ml/tuning.py b/python/pyspark/ml/tuning.py index f857c5e8c8..298314d46c 100644 --- a/python/pyspark/ml/tuning.py +++ b/python/pyspark/ml/tuning.py @@ -33,8 +33,6 @@ __all__ = ['ParamGridBuilder', 'CrossValidator', 'CrossValidatorModel', 'TrainVa class ParamGridBuilder(object): r""" - .. note:: Experimental - Builder for a param grid used in grid search-based model selection. >>> from pyspark.ml.classification import LogisticRegression @@ -145,8 +143,6 @@ class ValidatorParams(HasSeed): class CrossValidator(Estimator, ValidatorParams): """ - .. note:: Experimental - K-fold cross validation. >>> from pyspark.ml.classification import LogisticRegression @@ -264,8 +260,6 @@ class CrossValidator(Estimator, ValidatorParams): class CrossValidatorModel(Model, ValidatorParams): """ - .. note:: Experimental - Model from k-fold cross validation. .. versionadded:: 1.4.0 -- cgit v1.2.3