spark-instrumented-optimizer/python/pyspark/mllib/__init__.py
Joseph K. Bradley 5ffd5d3838 [SPARK-14817][ML][MLLIB][DOC] Made DataFrame-based API primary in MLlib guide
## What changes were proposed in this pull request?

Made DataFrame-based API primary
* Spark doc menu bar and other places now link to ml-guide.html, not mllib-guide.html
* mllib-guide.html keeps RDD-specific list of features, with a link at the top redirecting people to ml-guide.html
* ml-guide.html includes a "maintenance mode" announcement about the RDD-based API
  * **Reviewers: please check this carefully**
* (minor) Titles for DF API no longer include "- spark.ml" suffix.  Titles for RDD API have "- RDD-based API" suffix
* Moved migration guide to ml-guide from mllib-guide
  * Also moved past guides from mllib-migration-guides to ml-migration-guides, with a redirect link on mllib-migration-guides
  * **Reviewers**: I did not change any of the content of the migration guides.

Reorganized DataFrame-based guide:
* ml-guide.html mimics the old mllib-guide.html page in terms of content: overview, migration guide, etc.
* Moved Pipeline description into ml-pipeline.html and moved tuning into ml-tuning.html
  * **Reviewers**: I did not change the content of these guides, except some intro text.
* Sidebar remains the same, but with pipeline and tuning sections added

Other:
* ml-classification-regression.html: Moved text about linear methods to new section in page

## How was this patch tested?

Generated docs locally

Author: Joseph K. Bradley <joseph@databricks.com>

Closes #14213 from jkbradley/ml-guide-2.0.
2016-07-15 13:38:23 -07:00

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Python

#
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# distributed under the License is distributed on an "AS IS" BASIS,
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"""
RDD-based machine learning APIs for Python (in maintenance mode).
The `pyspark.mllib` package is in maintenance mode as of the Spark 2.0.0 release to encourage
migration to the DataFrame-based APIs under the `pyspark.ml` package.
"""
from __future__ import absolute_import
# MLlib currently needs NumPy 1.4+, so complain if lower
import numpy
ver = [int(x) for x in numpy.version.version.split('.')[:2]]
if ver < [1, 4]:
raise Exception("MLlib requires NumPy 1.4+")
__all__ = ['classification', 'clustering', 'feature', 'fpm', 'linalg', 'random',
'recommendation', 'regression', 'stat', 'tree', 'util']