diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py
index 6ef119a4265fdfc2afbaf7075f0f762f4fd8e10f..7051798485e2004aad665875aca9a3b329261021 100644
--- a/python/pyspark/ml/classification.py
+++ b/python/pyspark/ml/classification.py
@@ -142,9 +142,8 @@ class LogisticRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredicti
Sets the value of :py:attr:`threshold`.
Clears value of :py:attr:`thresholds` if it has been set.
"""
- self._paramMap[self.threshold] = value
- if self.isSet(self.thresholds):
- del self._paramMap[self.thresholds]
+ self._set(threshold=value)
+ self._clear(self.thresholds)
return self
@since("1.4.0")
@@ -169,9 +168,8 @@ class LogisticRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredicti
Sets the value of :py:attr:`thresholds`.
Clears value of :py:attr:`threshold` if it has been set.
"""
- self._paramMap[self.thresholds] = value
- if self.isSet(self.threshold):
- del self._paramMap[self.threshold]
+ self._set(thresholds=value)
+ self._clear(self.threshold)
return self
@since("1.5.0")
@@ -471,7 +469,7 @@ class TreeClassifierParams(object):
"""
Sets the value of :py:attr:`impurity`.
"""
- self._paramMap[self.impurity] = value
+ self._set(impurity=value)
return self
@since("1.6.0")
@@ -833,7 +831,7 @@ class GBTClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol
"""
Sets the value of :py:attr:`lossType`.
"""
- self._paramMap[self.lossType] = value
+ self._set(lossType=value)
return self
@since("1.4.0")
@@ -963,7 +961,7 @@ class NaiveBayes(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, H
"""
Sets the value of :py:attr:`smoothing`.
"""
- self._paramMap[self.smoothing] = value
+ self._set(smoothing=value)
return self
@since("1.5.0")
@@ -978,7 +976,7 @@ class NaiveBayes(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, H
"""
Sets the value of :py:attr:`modelType`.
"""
- self._paramMap[self.modelType] = value
+ self._set(modelType=value)
return self
@since("1.5.0")
@@ -1108,7 +1106,7 @@ class MultilayerPerceptronClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol,
"""
Sets the value of :py:attr:`layers`.
"""
- self._paramMap[self.layers] = value
+ self._set(layers=value)
return self
@since("1.6.0")
@@ -1123,7 +1121,7 @@ class MultilayerPerceptronClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol,
"""
Sets the value of :py:attr:`blockSize`.
"""
- self._paramMap[self.blockSize] = value
+ self._set(blockSize=value)
return self
@since("1.6.0")
diff --git a/python/pyspark/ml/clustering.py b/python/pyspark/ml/clustering.py
index f071c597c87f36b3414bb53eb24711667aece9cc..64c4bf1b927d7ae1fcd86232d29caa3e5a31a956 100644
--- a/python/pyspark/ml/clustering.py
+++ b/python/pyspark/ml/clustering.py
@@ -130,7 +130,7 @@ class KMeans(JavaEstimator, HasFeaturesCol, HasPredictionCol, HasMaxIter, HasTol
"""
Sets the value of :py:attr:`k`.
"""
- self._paramMap[self.k] = value
+ self._set(k=value)
return self
@since("1.5.0")
@@ -145,7 +145,7 @@ class KMeans(JavaEstimator, HasFeaturesCol, HasPredictionCol, HasMaxIter, HasTol
"""
Sets the value of :py:attr:`initMode`.
"""
- self._paramMap[self.initMode] = value
+ self._set(initMode=value)
return self
@since("1.5.0")
@@ -160,7 +160,7 @@ class KMeans(JavaEstimator, HasFeaturesCol, HasPredictionCol, HasMaxIter, HasTol
"""
Sets the value of :py:attr:`initSteps`.
"""
- self._paramMap[self.initSteps] = value
+ self._set(initSteps=value)
return self
@since("1.5.0")
@@ -280,7 +280,7 @@ class BisectingKMeans(JavaEstimator, HasFeaturesCol, HasPredictionCol, HasMaxIte
"""
Sets the value of :py:attr:`k`.
"""
- self._paramMap[self.k] = value
+ self._set(k=value)
return self
@since("2.0.0")
@@ -295,7 +295,7 @@ class BisectingKMeans(JavaEstimator, HasFeaturesCol, HasPredictionCol, HasMaxIte
"""
Sets the value of :py:attr:`minDivisibleClusterSize`.
"""
- self._paramMap[self.minDivisibleClusterSize] = value
+ self._set(minDivisibleClusterSize=value)
return self
@since("2.0.0")
diff --git a/python/pyspark/ml/evaluation.py b/python/pyspark/ml/evaluation.py
index 4b0bade10280241178c8553a51f79bae9ff36767..52a3fe898574766bd170531415e4a07309390129 100644
--- a/python/pyspark/ml/evaluation.py
+++ b/python/pyspark/ml/evaluation.py
@@ -19,7 +19,7 @@ from abc import abstractmethod, ABCMeta
from pyspark import since
from pyspark.ml.wrapper import JavaParams
-from pyspark.ml.param import Param, Params
+from pyspark.ml.param import Param, Params, TypeConverters
from pyspark.ml.param.shared import HasLabelCol, HasPredictionCol, HasRawPredictionCol
from pyspark.ml.util import keyword_only
from pyspark.mllib.common import inherit_doc
@@ -125,7 +125,8 @@ class BinaryClassificationEvaluator(JavaEvaluator, HasLabelCol, HasRawPrediction
"""
metricName = Param(Params._dummy(), "metricName",
- "metric name in evaluation (areaUnderROC|areaUnderPR)")
+ "metric name in evaluation (areaUnderROC|areaUnderPR)",
+ typeConverter=TypeConverters.toString)
@keyword_only
def __init__(self, rawPredictionCol="rawPrediction", labelCol="label",
@@ -147,7 +148,7 @@ class BinaryClassificationEvaluator(JavaEvaluator, HasLabelCol, HasRawPrediction
"""
Sets the value of :py:attr:`metricName`.
"""
- self._paramMap[self.metricName] = value
+ self._set(metricName=value)
return self
@since("1.4.0")
@@ -194,7 +195,8 @@ class RegressionEvaluator(JavaEvaluator, HasLabelCol, HasPredictionCol):
# when we evaluate a metric that is needed to minimize (e.g., `"rmse"`, `"mse"`, `"mae"`),
# we take and output the negative of this metric.
metricName = Param(Params._dummy(), "metricName",
- "metric name in evaluation (mse|rmse|r2|mae)")
+ "metric name in evaluation (mse|rmse|r2|mae)",
+ typeConverter=TypeConverters.toString)
@keyword_only
def __init__(self, predictionCol="prediction", labelCol="label",
@@ -216,7 +218,7 @@ class RegressionEvaluator(JavaEvaluator, HasLabelCol, HasPredictionCol):
"""
Sets the value of :py:attr:`metricName`.
"""
- self._paramMap[self.metricName] = value
+ self._set(metricName=value)
return self
@since("1.4.0")
@@ -260,7 +262,8 @@ class MulticlassClassificationEvaluator(JavaEvaluator, HasLabelCol, HasPredictio
"""
metricName = Param(Params._dummy(), "metricName",
"metric name in evaluation "
- "(f1|precision|recall|weightedPrecision|weightedRecall)")
+ "(f1|precision|recall|weightedPrecision|weightedRecall)",
+ typeConverter=TypeConverters.toString)
@keyword_only
def __init__(self, predictionCol="prediction", labelCol="label",
@@ -282,7 +285,7 @@ class MulticlassClassificationEvaluator(JavaEvaluator, HasLabelCol, HasPredictio
"""
Sets the value of :py:attr:`metricName`.
"""
- self._paramMap[self.metricName] = value
+ self._set(metricName=value)
return self
@since("1.5.0")
diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py
index 0d8ef1297f18c89cd8d257702ce4300ae76d9988..776906eaab79b9a924ccb9220bb6165a7507fd5c 100644
--- a/python/pyspark/ml/feature.py
+++ b/python/pyspark/ml/feature.py
@@ -19,6 +19,8 @@ import sys
if sys.version > '3':
basestring = str
+from py4j.java_collections import JavaArray
+
from pyspark import since
from pyspark.rdd import ignore_unicode_prefix
from pyspark.ml.param.shared import *
@@ -112,7 +114,7 @@ class Binarizer(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable, Java
"""
Sets the value of :py:attr:`threshold`.
"""
- self._paramMap[self.threshold] = value
+ self._set(threshold=value)
return self
@since("1.4.0")
@@ -188,7 +190,7 @@ class Bucketizer(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable, Jav
"""
Sets the value of :py:attr:`splits`.
"""
- self._paramMap[self.splits] = value
+ self._set(splits=value)
return self
@since("1.4.0")
@@ -293,7 +295,7 @@ class CountVectorizer(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable,
"""
Sets the value of :py:attr:`minTF`.
"""
- self._paramMap[self.minTF] = value
+ self._set(minTF=value)
return self
@since("1.6.0")
@@ -308,7 +310,7 @@ class CountVectorizer(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable,
"""
Sets the value of :py:attr:`minDF`.
"""
- self._paramMap[self.minDF] = value
+ self._set(minDF=value)
return self
@since("1.6.0")
@@ -323,7 +325,7 @@ class CountVectorizer(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable,
"""
Sets the value of :py:attr:`vocabSize`.
"""
- self._paramMap[self.vocabSize] = value
+ self._set(vocabSize=value)
return self
@since("1.6.0")
@@ -431,7 +433,7 @@ class DCT(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable, JavaMLWrit
"""
Sets the value of :py:attr:`inverse`.
"""
- self._paramMap[self.inverse] = value
+ self._set(inverse=value)
return self
@since("1.6.0")
@@ -498,7 +500,7 @@ class ElementwiseProduct(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReada
"""
Sets the value of :py:attr:`scalingVec`.
"""
- self._paramMap[self.scalingVec] = value
+ self._set(scalingVec=value)
return self
@since("1.5.0")
@@ -641,7 +643,7 @@ class IDF(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, JavaMLWritab
"""
Sets the value of :py:attr:`minDocFreq`.
"""
- self._paramMap[self.minDocFreq] = value
+ self._set(minDocFreq=value)
return self
@since("1.4.0")
@@ -826,7 +828,7 @@ class MinMaxScaler(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, Jav
"""
Sets the value of :py:attr:`min`.
"""
- self._paramMap[self.min] = value
+ self._set(min=value)
return self
@since("1.6.0")
@@ -841,7 +843,7 @@ class MinMaxScaler(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, Jav
"""
Sets the value of :py:attr:`max`.
"""
- self._paramMap[self.max] = value
+ self._set(max=value)
return self
@since("1.6.0")
@@ -950,7 +952,7 @@ class NGram(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable, JavaMLWr
"""
Sets the value of :py:attr:`n`.
"""
- self._paramMap[self.n] = value
+ self._set(n=value)
return self
@since("1.5.0")
@@ -1017,7 +1019,7 @@ class Normalizer(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable, Jav
"""
Sets the value of :py:attr:`p`.
"""
- self._paramMap[self.p] = value
+ self._set(p=value)
return self
@since("1.4.0")
@@ -1100,7 +1102,7 @@ class OneHotEncoder(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable,
"""
Sets the value of :py:attr:`dropLast`.
"""
- self._paramMap[self.dropLast] = value
+ self._set(dropLast=value)
return self
@since("1.4.0")
@@ -1169,7 +1171,7 @@ class PolynomialExpansion(JavaTransformer, HasInputCol, HasOutputCol, JavaMLRead
"""
Sets the value of :py:attr:`degree`.
"""
- self._paramMap[self.degree] = value
+ self._set(degree=value)
return self
@since("1.4.0")
@@ -1251,7 +1253,7 @@ class QuantileDiscretizer(JavaEstimator, HasInputCol, HasOutputCol, HasSeed, Jav
"""
Sets the value of :py:attr:`numBuckets`.
"""
- self._paramMap[self.numBuckets] = value
+ self._set(numBuckets=value)
return self
@since("2.0.0")
@@ -1349,7 +1351,7 @@ class RegexTokenizer(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable,
"""
Sets the value of :py:attr:`minTokenLength`.
"""
- self._paramMap[self.minTokenLength] = value
+ self._set(minTokenLength=value)
return self
@since("1.4.0")
@@ -1364,7 +1366,7 @@ class RegexTokenizer(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable,
"""
Sets the value of :py:attr:`gaps`.
"""
- self._paramMap[self.gaps] = value
+ self._set(gaps=value)
return self
@since("1.4.0")
@@ -1379,7 +1381,7 @@ class RegexTokenizer(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable,
"""
Sets the value of :py:attr:`pattern`.
"""
- self._paramMap[self.pattern] = value
+ self._set(pattern=value)
return self
@since("1.4.0")
@@ -1394,7 +1396,7 @@ class RegexTokenizer(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable,
"""
Sets the value of :py:attr:`toLowercase`.
"""
- self._paramMap[self.toLowercase] = value
+ self._set(toLowercase=value)
return self
@since("2.0.0")
@@ -1455,7 +1457,7 @@ class SQLTransformer(JavaTransformer, JavaMLReadable, JavaMLWritable):
"""
Sets the value of :py:attr:`statement`.
"""
- self._paramMap[self.statement] = value
+ self._set(statement=value)
return self
@since("1.6.0")
@@ -1532,7 +1534,7 @@ class StandardScaler(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, J
"""
Sets the value of :py:attr:`withMean`.
"""
- self._paramMap[self.withMean] = value
+ self._set(withMean=value)
return self
@since("1.4.0")
@@ -1547,7 +1549,7 @@ class StandardScaler(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, J
"""
Sets the value of :py:attr:`withStd`.
"""
- self._paramMap[self.withStd] = value
+ self._set(withStd=value)
return self
@since("1.4.0")
@@ -1598,7 +1600,7 @@ class StringIndexer(JavaEstimator, HasInputCol, HasOutputCol, HasHandleInvalid,
The indices are in [0, numLabels), ordered by label frequencies.
So the most frequent label gets index 0.
- >>> stringIndexer = StringIndexer(inputCol="label", outputCol="indexed")
+ >>> stringIndexer = StringIndexer(inputCol="label", outputCol="indexed", handleInvalid='error')
>>> model = stringIndexer.fit(stringIndDf)
>>> td = model.transform(stringIndDf)
>>> sorted(set([(i[0], i[1]) for i in td.select(td.id, td.indexed).collect()]),
@@ -1716,7 +1718,7 @@ class IndexToString(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable,
"""
Sets the value of :py:attr:`labels`.
"""
- self._paramMap[self.labels] = value
+ self._set(labels=value)
return self
@since("1.6.0")
@@ -1787,7 +1789,7 @@ class StopWordsRemover(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadabl
"""
Specify the stopwords to be filtered.
"""
- self._paramMap[self.stopWords] = value
+ self._set(stopWords=value)
return self
@since("1.6.0")
@@ -1802,7 +1804,7 @@ class StopWordsRemover(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadabl
"""
Set whether to do a case sensitive comparison over the stop words
"""
- self._paramMap[self.caseSensitive] = value
+ self._set(caseSensitive=value)
return self
@since("1.6.0")
@@ -2019,7 +2021,7 @@ class VectorIndexer(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, Ja
"""
Sets the value of :py:attr:`maxCategories`.
"""
- self._paramMap[self.maxCategories] = value
+ self._set(maxCategories=value)
return self
@since("1.4.0")
@@ -2129,7 +2131,7 @@ class VectorSlicer(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable, J
"""
Sets the value of :py:attr:`indices`.
"""
- self._paramMap[self.indices] = value
+ self._set(indices=value)
return self
@since("1.6.0")
@@ -2144,7 +2146,7 @@ class VectorSlicer(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable, J
"""
Sets the value of :py:attr:`names`.
"""
- self._paramMap[self.names] = value
+ self._set(names=value)
return self
@since("1.6.0")
@@ -2249,7 +2251,7 @@ class Word2Vec(JavaEstimator, HasStepSize, HasMaxIter, HasSeed, HasInputCol, Has
"""
Sets the value of :py:attr:`vectorSize`.
"""
- self._paramMap[self.vectorSize] = value
+ self._set(vectorSize=value)
return self
@since("1.4.0")
@@ -2264,7 +2266,7 @@ class Word2Vec(JavaEstimator, HasStepSize, HasMaxIter, HasSeed, HasInputCol, Has
"""
Sets the value of :py:attr:`numPartitions`.
"""
- self._paramMap[self.numPartitions] = value
+ self._set(numPartitions=value)
return self
@since("1.4.0")
@@ -2279,7 +2281,7 @@ class Word2Vec(JavaEstimator, HasStepSize, HasMaxIter, HasSeed, HasInputCol, Has
"""
Sets the value of :py:attr:`minCount`.
"""
- self._paramMap[self.minCount] = value
+ self._set(minCount=value)
return self
@since("1.4.0")
@@ -2385,7 +2387,7 @@ class PCA(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadable, JavaMLWritab
"""
Sets the value of :py:attr:`k`.
"""
- self._paramMap[self.k] = value
+ self._set(k=value)
return self
@since("1.5.0")
@@ -2517,7 +2519,7 @@ class RFormula(JavaEstimator, HasFeaturesCol, HasLabelCol, JavaMLReadable, JavaM
"""
Sets the value of :py:attr:`formula`.
"""
- self._paramMap[self.formula] = value
+ self._set(formula=value)
return self
@since("1.5.0")
@@ -2609,7 +2611,7 @@ class ChiSqSelector(JavaEstimator, HasFeaturesCol, HasOutputCol, HasLabelCol, Ja
"""
Sets the value of :py:attr:`numTopFeatures`.
"""
- self._paramMap[self.numTopFeatures] = value
+ self._set(numTopFeatures=value)
return self
@since("2.0.0")
diff --git a/python/pyspark/ml/param/__init__.py b/python/pyspark/ml/param/__init__.py
index a1265294a1e9e0dd6f7e15dff823968a6cbbb9af..9f0b063aace5af0b927312fce84b74bca5e02539 100644
--- a/python/pyspark/ml/param/__init__.py
+++ b/python/pyspark/ml/param/__init__.py
@@ -26,6 +26,8 @@ import copy
import numpy as np
import warnings
+from py4j.java_gateway import JavaObject
+
from pyspark import since
from pyspark.ml.util import Identifiable
from pyspark.mllib.linalg import DenseVector, Vector
@@ -389,8 +391,8 @@ class Params(Identifiable):
if extra is None:
extra = dict()
that = copy.copy(self)
- that._paramMap = self.extractParamMap(extra)
- return that
+ that._paramMap = {}
+ return self._copyValues(that, extra)
def _shouldOwn(self, param):
"""
@@ -439,12 +441,26 @@ class Params(Identifiable):
self._paramMap[p] = value
return self
+ def _clear(self, param):
+ """
+ Clears a param from the param map if it has been explicitly set.
+ """
+ if self.isSet(param):
+ del self._paramMap[param]
+
def _setDefault(self, **kwargs):
"""
Sets default params.
"""
for param, value in kwargs.items():
- self._defaultParamMap[getattr(self, param)] = value
+ p = getattr(self, param)
+ if value is not None and not isinstance(value, JavaObject):
+ try:
+ value = p.typeConverter(value)
+ except TypeError as e:
+ raise TypeError('Invalid default param value given for param "%s". %s'
+ % (p.name, e))
+ self._defaultParamMap[p] = value
return self
def _copyValues(self, to, extra=None):
diff --git a/python/pyspark/ml/param/_shared_params_code_gen.py b/python/pyspark/ml/param/_shared_params_code_gen.py
index a7615c43bee24ac7e00c855d6ee866c82d6fdcbb..a2acf956bc2adc6c1f9fe81421daba840be71ead 100644
--- a/python/pyspark/ml/param/_shared_params_code_gen.py
+++ b/python/pyspark/ml/param/_shared_params_code_gen.py
@@ -131,7 +131,7 @@ if __name__ == "__main__":
"TypeConverters.toFloat"),
("handleInvalid", "how to handle invalid entries. Options are skip (which will filter " +
"out rows with bad values), or error (which will throw an errror). More options may be " +
- "added later.", None, "TypeConverters.toBoolean"),
+ "added later.", None, "TypeConverters.toString"),
("elasticNetParam", "the ElasticNet mixing parameter, in range [0, 1]. For alpha = 0, " +
"the penalty is an L2 penalty. For alpha = 1, it is an L1 penalty.", "0.0",
"TypeConverters.toFloat"),
diff --git a/python/pyspark/ml/param/shared.py b/python/pyspark/ml/param/shared.py
index c9e975525ce1f55a1396b090d606849038f2f288..538c0b718ad9b7c32cc048eab3fc16adedf00682 100644
--- a/python/pyspark/ml/param/shared.py
+++ b/python/pyspark/ml/param/shared.py
@@ -392,7 +392,7 @@ class HasHandleInvalid(Params):
Mixin for param handleInvalid: how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an errror). More options may be added later.
"""
- handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an errror). More options may be added later.", typeConverter=TypeConverters.toBoolean)
+ handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an errror). More options may be added later.", typeConverter=TypeConverters.toString)
def __init__(self):
super(HasHandleInvalid, self).__init__()
diff --git a/python/pyspark/ml/pipeline.py b/python/pyspark/ml/pipeline.py
index 9d654e8b0f8d063cf9b1c8ba621c5ea587024313..6f599b51596fb28a090ffd0831a810d876fa56ad 100644
--- a/python/pyspark/ml/pipeline.py
+++ b/python/pyspark/ml/pipeline.py
@@ -90,7 +90,7 @@ class Pipeline(Estimator, MLReadable, MLWritable):
:param value: a list of transformers or estimators
:return: the pipeline instance
"""
- self._paramMap[self.stages] = value
+ self._set(stages=value)
return self
@since("1.3.0")
diff --git a/python/pyspark/ml/recommendation.py b/python/pyspark/ml/recommendation.py
index 7c7a1b67a100e1dfb2215f3932852b909a133429..9c38f2431b8d0681c427617b6b47d782a8d81620 100644
--- a/python/pyspark/ml/recommendation.py
+++ b/python/pyspark/ml/recommendation.py
@@ -157,7 +157,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha
"""
Sets the value of :py:attr:`rank`.
"""
- self._paramMap[self.rank] = value
+ self._set(rank=value)
return self
@since("1.4.0")
@@ -172,7 +172,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha
"""
Sets the value of :py:attr:`numUserBlocks`.
"""
- self._paramMap[self.numUserBlocks] = value
+ self._set(numUserBlocks=value)
return self
@since("1.4.0")
@@ -187,7 +187,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha
"""
Sets the value of :py:attr:`numItemBlocks`.
"""
- self._paramMap[self.numItemBlocks] = value
+ self._set(numItemBlocks=value)
return self
@since("1.4.0")
@@ -202,15 +202,15 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha
"""
Sets both :py:attr:`numUserBlocks` and :py:attr:`numItemBlocks` to the specific value.
"""
- self._paramMap[self.numUserBlocks] = value
- self._paramMap[self.numItemBlocks] = value
+ self._set(numUserBlocks=value)
+ self._set(numItemBlocks=value)
@since("1.4.0")
def setImplicitPrefs(self, value):
"""
Sets the value of :py:attr:`implicitPrefs`.
"""
- self._paramMap[self.implicitPrefs] = value
+ self._set(implicitPrefs=value)
return self
@since("1.4.0")
@@ -225,7 +225,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha
"""
Sets the value of :py:attr:`alpha`.
"""
- self._paramMap[self.alpha] = value
+ self._set(alpha=value)
return self
@since("1.4.0")
@@ -240,7 +240,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha
"""
Sets the value of :py:attr:`userCol`.
"""
- self._paramMap[self.userCol] = value
+ self._set(userCol=value)
return self
@since("1.4.0")
@@ -255,7 +255,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha
"""
Sets the value of :py:attr:`itemCol`.
"""
- self._paramMap[self.itemCol] = value
+ self._set(itemCol=value)
return self
@since("1.4.0")
@@ -270,7 +270,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha
"""
Sets the value of :py:attr:`ratingCol`.
"""
- self._paramMap[self.ratingCol] = value
+ self._set(ratingCol=value)
return self
@since("1.4.0")
@@ -285,7 +285,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha
"""
Sets the value of :py:attr:`nonnegative`.
"""
- self._paramMap[self.nonnegative] = value
+ self._set(nonnegative=value)
return self
@since("1.4.0")
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py
index 3c7852526a4812a5c9e833d67557aec3f99396ae..8b686225243043aad4d46f33fb3c6da6d503a84f 100644
--- a/python/pyspark/ml/regression.py
+++ b/python/pyspark/ml/regression.py
@@ -478,7 +478,7 @@ class IsotonicRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredicti
"""
Sets the value of :py:attr:`isotonic`.
"""
- self._paramMap[self.isotonic] = value
+ self._set(isotonic=value)
return self
def getIsotonic(self):
@@ -491,7 +491,7 @@ class IsotonicRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredicti
"""
Sets the value of :py:attr:`featureIndex`.
"""
- self._paramMap[self.featureIndex] = value
+ self._set(featureIndex=value)
return self
def getFeatureIndex(self):
@@ -541,7 +541,7 @@ class TreeEnsembleParams(DecisionTreeParams):
"""
Sets the value of :py:attr:`subsamplingRate`.
"""
- self._paramMap[self.subsamplingRate] = value
+ self._set(subsamplingRate=value)
return self
@since("1.4.0")
@@ -571,7 +571,7 @@ class TreeRegressorParams(Params):
"""
Sets the value of :py:attr:`impurity`.
"""
- self._paramMap[self.impurity] = value
+ self._set(impurity=value)
return self
@since("1.4.0")
@@ -604,7 +604,7 @@ class RandomForestParams(TreeEnsembleParams):
"""
Sets the value of :py:attr:`numTrees`.
"""
- self._paramMap[self.numTrees] = value
+ self._set(numTrees=value)
return self
@since("1.4.0")
@@ -619,7 +619,7 @@ class RandomForestParams(TreeEnsembleParams):
"""
Sets the value of :py:attr:`featureSubsetStrategy`.
"""
- self._paramMap[self.featureSubsetStrategy] = value
+ self._set(featureSubsetStrategy=value)
return self
@since("1.4.0")
@@ -991,7 +991,7 @@ class GBTRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol,
"""
Sets the value of :py:attr:`lossType`.
"""
- self._paramMap[self.lossType] = value
+ self._set(lossType=value)
return self
@since("1.4.0")
@@ -1126,7 +1126,7 @@ class AFTSurvivalRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredi
"""
Sets the value of :py:attr:`censorCol`.
"""
- self._paramMap[self.censorCol] = value
+ self._set(censorCol=value)
return self
@since("1.6.0")
@@ -1141,7 +1141,7 @@ class AFTSurvivalRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredi
"""
Sets the value of :py:attr:`quantileProbabilities`.
"""
- self._paramMap[self.quantileProbabilities] = value
+ self._set(quantileProbabilities=value)
return self
@since("1.6.0")
@@ -1156,7 +1156,7 @@ class AFTSurvivalRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredi
"""
Sets the value of :py:attr:`quantilesCol`.
"""
- self._paramMap[self.quantilesCol] = value
+ self._set(quantilesCol=value)
return self
@since("1.6.0")
@@ -1305,7 +1305,7 @@ class GeneralizedLinearRegression(JavaEstimator, HasLabelCol, HasFeaturesCol, Ha
"""
Sets the value of :py:attr:`family`.
"""
- self._paramMap[self.family] = value
+ self._set(family=value)
return self
@since("2.0.0")
@@ -1320,7 +1320,7 @@ class GeneralizedLinearRegression(JavaEstimator, HasLabelCol, HasFeaturesCol, Ha
"""
Sets the value of :py:attr:`link`.
"""
- self._paramMap[self.link] = value
+ self._set(link=value)
return self
@since("2.0.0")
diff --git a/python/pyspark/ml/tuning.py b/python/pyspark/ml/tuning.py
index 456d79d897e003b7a199199b26af2ea78b43aa03..5ac539eddea5d1a78a077d746e21c40dce8d0ba4 100644
--- a/python/pyspark/ml/tuning.py
+++ b/python/pyspark/ml/tuning.py
@@ -228,7 +228,7 @@ class CrossValidator(Estimator, ValidatorParams, MLReadable, MLWritable):
"""
Sets the value of :py:attr:`numFolds`.
"""
- self._paramMap[self.numFolds] = value
+ self._set(numFolds=value)
return self
@since("1.4.0")
@@ -479,7 +479,7 @@ class TrainValidationSplit(Estimator, ValidatorParams, MLReadable, MLWritable):
"""
Sets the value of :py:attr:`trainRatio`.
"""
- self._paramMap[self.trainRatio] = value
+ self._set(trainRatio=value)
return self
@since("2.0.0")
diff --git a/python/pyspark/ml/wrapper.py b/python/pyspark/ml/wrapper.py
index cd0e5b80d555943a1614b8f84f99552c14e22a14..055a2816f8d753e137feeeb9f93b96f81b0469c0 100644
--- a/python/pyspark/ml/wrapper.py
+++ b/python/pyspark/ml/wrapper.py
@@ -112,7 +112,7 @@ class JavaParams(JavaWrapper, Params):
java_param = self._java_obj.getParam(param.name)
if self._java_obj.isDefined(java_param):
value = _java2py(sc, self._java_obj.getOrDefault(java_param))
- self._paramMap[param] = value
+ self._set(**{param.name: value})
def _transfer_param_map_from_java(self, javaParamMap):
"""