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authorJoseph K. Bradley <joseph@databricks.com>2017-02-02 11:58:46 -0800
committerJoseph K. Bradley <joseph@databricks.com>2017-02-02 11:58:46 -0800
commit1d5d2a9d0940d05444b76005f3548f96ecfbde95 (patch)
tree9edc32503554b5e6592d878664d82f76b57c5431 /python
parent8303e20c45153f91e585e230caa29b728a4d8c6c (diff)
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[SPARK-19389][ML][PYTHON][DOC] Minor doc fixes for ML Python Params and LinearSVC
## What changes were proposed in this pull request? * Removed Since tags in Python Params since they are inherited by other classes * Fixed doc links for LinearSVC ## How was this patch tested? * doc tests * generating docs locally and checking manually Author: Joseph K. Bradley <joseph@databricks.com> Closes #16723 from jkbradley/pyparam-fix-doc.
Diffstat (limited to 'python')
-rw-r--r--python/pyspark/ml/classification.py9
-rw-r--r--python/pyspark/ml/param/__init__.py13
2 files changed, 5 insertions, 17 deletions
diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py
index d41fc81fd7..69f0cea82e 100644
--- a/python/pyspark/ml/classification.py
+++ b/python/pyspark/ml/classification.py
@@ -65,7 +65,10 @@ class LinearSVC(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, Ha
HasRegParam, HasTol, HasRawPredictionCol, HasFitIntercept, HasStandardization,
HasThreshold, HasWeightCol, HasAggregationDepth, JavaMLWritable, JavaMLReadable):
"""
+ .. note:: Experimental
+
`Linear SVM Classifier <https://en.wikipedia.org/wiki/Support_vector_machine#Linear_SVM>`_
+
This binary classifier optimizes the Hinge Loss using the OWLQN optimizer.
>>> from pyspark.sql import Row
@@ -89,10 +92,6 @@ class LinearSVC(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, Ha
1.0
>>> result.rawPrediction
DenseVector([-1.4831, 1.4831])
- >>> svm.setParams("vector")
- Traceback (most recent call last):
- ...
- TypeError: Method setParams forces keyword arguments.
>>> svm_path = temp_path + "/svm"
>>> svm.save(svm_path)
>>> svm2 = LinearSVC.load(svm_path)
@@ -150,6 +149,8 @@ class LinearSVC(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, Ha
class LinearSVCModel(JavaModel, JavaClassificationModel, JavaMLWritable, JavaMLReadable):
"""
+ .. note:: Experimental
+
Model fitted by LinearSVC.
.. versionadded:: 2.2.0
diff --git a/python/pyspark/ml/param/__init__.py b/python/pyspark/ml/param/__init__.py
index ade4864e1d..dc3d23ff16 100644
--- a/python/pyspark/ml/param/__init__.py
+++ b/python/pyspark/ml/param/__init__.py
@@ -24,11 +24,9 @@ if sys.version > '3':
from abc import ABCMeta
import copy
import numpy as np
-import warnings
from py4j.java_gateway import JavaObject
-from pyspark import since
from pyspark.ml.linalg import DenseVector, Vector
from pyspark.ml.util import Identifiable
@@ -251,7 +249,6 @@ class Params(Identifiable):
setattr(self, name, param._copy_new_parent(self))
@property
- @since("1.3.0")
def params(self):
"""
Returns all params ordered by name. The default implementation
@@ -264,7 +261,6 @@ class Params(Identifiable):
not isinstance(getattr(type(self), x, None), property)]))
return self._params
- @since("1.4.0")
def explainParam(self, param):
"""
Explains a single param and returns its name, doc, and optional
@@ -282,7 +278,6 @@ class Params(Identifiable):
valueStr = "(" + ", ".join(values) + ")"
return "%s: %s %s" % (param.name, param.doc, valueStr)
- @since("1.4.0")
def explainParams(self):
"""
Returns the documentation of all params with their optionally
@@ -290,7 +285,6 @@ class Params(Identifiable):
"""
return "\n".join([self.explainParam(param) for param in self.params])
- @since("1.4.0")
def getParam(self, paramName):
"""
Gets a param by its name.
@@ -301,7 +295,6 @@ class Params(Identifiable):
else:
raise ValueError("Cannot find param with name %s." % paramName)
- @since("1.4.0")
def isSet(self, param):
"""
Checks whether a param is explicitly set by user.
@@ -309,7 +302,6 @@ class Params(Identifiable):
param = self._resolveParam(param)
return param in self._paramMap
- @since("1.4.0")
def hasDefault(self, param):
"""
Checks whether a param has a default value.
@@ -317,7 +309,6 @@ class Params(Identifiable):
param = self._resolveParam(param)
return param in self._defaultParamMap
- @since("1.4.0")
def isDefined(self, param):
"""
Checks whether a param is explicitly set by user or has
@@ -325,7 +316,6 @@ class Params(Identifiable):
"""
return self.isSet(param) or self.hasDefault(param)
- @since("1.4.0")
def hasParam(self, paramName):
"""
Tests whether this instance contains a param with a given
@@ -337,7 +327,6 @@ class Params(Identifiable):
else:
raise TypeError("hasParam(): paramName must be a string")
- @since("1.4.0")
def getOrDefault(self, param):
"""
Gets the value of a param in the user-supplied param map or its
@@ -349,7 +338,6 @@ class Params(Identifiable):
else:
return self._defaultParamMap[param]
- @since("1.4.0")
def extractParamMap(self, extra=None):
"""
Extracts the embedded default param values and user-supplied
@@ -368,7 +356,6 @@ class Params(Identifiable):
paramMap.update(extra)
return paramMap
- @since("1.4.0")
def copy(self, extra=None):
"""
Creates a copy of this instance with the same uid and some