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authorHolden Karau <holden@us.ibm.com>2016-05-24 22:20:00 -0700
committerShivaram Venkataraman <shivaram@cs.berkeley.edu>2016-05-24 22:20:00 -0700
commitcd9f16906cabd012b7676eb0f524e68a9cbe4db1 (patch)
tree89e07b90a3ffd87e4c6ff765a7694e11502ab153
parentc9c1c0e54d34773ac2cf5457fe5925559ece36c7 (diff)
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[SPARK-15412][PYSPARK][SPARKR][DOCS] Improve linear isotonic regression pydoc & doc build insturctions
## What changes were proposed in this pull request? PySpark: Add links to the predictors from the models in regression.py, improve linear and isotonic pydoc in minor ways. User guide / R: Switch the installed package list to be enough to build the R docs on a "fresh" install on ubuntu and add sudo to match the rest of the commands. User Guide: Add a note about using gem2.0 for systems with both 1.9 and 2.0 (e.g. some ubuntu but maybe more). ## How was this patch tested? built pydocs locally, tested new user build instructions Author: Holden Karau <holden@us.ibm.com> Closes #13199 from holdenk/SPARK-15412-improve-linear-isotonic-regression-pydoc.
-rw-r--r--docs/README.md4
-rw-r--r--python/pyspark/ml/regression.py30
2 files changed, 20 insertions, 14 deletions
diff --git a/docs/README.md b/docs/README.md
index bcea93e1f3..8b515e1873 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -20,8 +20,10 @@ installed. Also install the following libraries:
$ sudo pip install Pygments
# Following is needed only for generating API docs
$ sudo pip install sphinx
- $ Rscript -e 'install.packages(c("knitr", "devtools"), repos="http://cran.stat.ucla.edu/")'
+ $ sudo Rscript -e 'install.packages(c("knitr", "devtools", "roxygen2", "testthat"), repos="http://cran.stat.ucla.edu/")'
```
+(Note: If you are on a system with both Ruby 1.9 and Ruby 2.0 you may need to replace gem with gem2.0)
+
## Generating the Documentation HTML
We include the Spark documentation as part of the source (as opposed to using a hosted wiki, such as
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py
index 8f58594a66..1b7af7ef59 100644
--- a/python/pyspark/ml/regression.py
+++ b/python/pyspark/ml/regression.py
@@ -48,11 +48,15 @@ class LinearRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPrediction
The learning objective is to minimize the squared error, with regularization.
The specific squared error loss function used is: L = 1/2n ||A coefficients - y||^2^
- This support multiple types of regularization:
- - none (a.k.a. ordinary least squares)
- - L2 (ridge regression)
- - L1 (Lasso)
- - L2 + L1 (elastic net)
+ This supports multiple types of regularization:
+
+ * none (a.k.a. ordinary least squares)
+
+ * L2 (ridge regression)
+
+ * L1 (Lasso)
+
+ * L2 + L1 (elastic net)
>>> from pyspark.ml.linalg import Vectors
>>> df = spark.createDataFrame([
@@ -128,7 +132,7 @@ class LinearRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
"""
.. note:: Experimental
- Model fitted by LinearRegression.
+ Model fitted by :class:`LinearRegression`.
.. versionadded:: 1.4.0
"""
@@ -503,13 +507,13 @@ class IsotonicRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
"""
.. note:: Experimental
- Model fitted by IsotonicRegression.
+ Model fitted by :class:`IsotonicRegression`.
"""
@property
def boundaries(self):
"""
- Model boundaries.
+ Boundaries in increasing order for which predictions are known.
"""
return self._call_java("boundaries")
@@ -769,7 +773,7 @@ class DecisionTreeRegressionModel(DecisionTreeModel, JavaMLWritable, JavaMLReada
"""
.. note:: Experimental
- Model fitted by DecisionTreeRegressor.
+ Model fitted by :class:`DecisionTreeRegressor`.
.. versionadded:: 1.4.0
"""
@@ -887,7 +891,7 @@ class RandomForestRegressionModel(TreeEnsembleModels, JavaMLWritable, JavaMLRead
"""
.. note:: Experimental
- Model fitted by RandomForestRegressor.
+ Model fitted by :class:`RandomForestRegressor`.
.. versionadded:: 1.4.0
"""
@@ -1021,7 +1025,7 @@ class GBTRegressionModel(TreeEnsembleModels, JavaMLWritable, JavaMLReadable):
"""
.. note:: Experimental
- Model fitted by GBTRegressor.
+ Model fitted by :class:`GBTRegressor`.
.. versionadded:: 1.4.0
"""
@@ -1190,7 +1194,7 @@ class AFTSurvivalRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
"""
.. note:: Experimental
- Model fitted by AFTSurvivalRegression.
+ Model fitted by :class:`AFTSurvivalRegression`.
.. versionadded:: 1.6.0
"""
@@ -1380,7 +1384,7 @@ class GeneralizedLinearRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable
"""
.. note:: Experimental
- Model fitted by GeneralizedLinearRegression.
+ Model fitted by :class:`GeneralizedLinearRegression`.
.. versionadded:: 2.0.0
"""