[SPARK-20606][ML] ML 2.2 QA: Remove deprecated methods for ML
## What changes were proposed in this pull request? Remove ML methods we deprecated in 2.1. ## How was this patch tested? Existing tests. Author: Yanbo Liang <ybliang8@gmail.com> Closes #17867 from yanboliang/spark-20606.
This commit is contained in:
Yanbo Liang
parent
be53a78352
commit
b8733e0ad9
|
|
@ -54,27 +54,27 @@ class DecisionTreeClassifier @Since("1.4.0") (
|
|||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
|
||||
/**
|
||||
* Specifies how often to checkpoint the cached node IDs.
|
||||
|
|
@ -86,15 +86,15 @@ class DecisionTreeClassifier @Since("1.4.0") (
|
|||
* @group setParam
|
||||
*/
|
||||
@Since("1.4.0")
|
||||
override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setImpurity(value: String): this.type = set(impurity, value)
|
||||
def setImpurity(value: String): this.type = set(impurity, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.6.0")
|
||||
override def setSeed(value: Long): this.type = set(seed, value)
|
||||
def setSeed(value: Long): this.type = set(seed, value)
|
||||
|
||||
override protected def train(dataset: Dataset[_]): DecisionTreeClassificationModel = {
|
||||
val categoricalFeatures: Map[Int, Int] =
|
||||
|
|
|
|||
|
|
@ -70,27 +70,27 @@ class GBTClassifier @Since("1.4.0") (
|
|||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
|
||||
/**
|
||||
* Specifies how often to checkpoint the cached node IDs.
|
||||
|
|
@ -102,7 +102,7 @@ class GBTClassifier @Since("1.4.0") (
|
|||
* @group setParam
|
||||
*/
|
||||
@Since("1.4.0")
|
||||
override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
|
||||
/**
|
||||
* The impurity setting is ignored for GBT models.
|
||||
|
|
@ -111,7 +111,7 @@ class GBTClassifier @Since("1.4.0") (
|
|||
* @group setParam
|
||||
*/
|
||||
@Since("1.4.0")
|
||||
override def setImpurity(value: String): this.type = {
|
||||
def setImpurity(value: String): this.type = {
|
||||
logWarning("GBTClassifier.setImpurity should NOT be used")
|
||||
this
|
||||
}
|
||||
|
|
@ -120,21 +120,21 @@ class GBTClassifier @Since("1.4.0") (
|
|||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
|
||||
def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setSeed(value: Long): this.type = set(seed, value)
|
||||
def setSeed(value: Long): this.type = set(seed, value)
|
||||
|
||||
// Parameters from GBTParams:
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxIter(value: Int): this.type = set(maxIter, value)
|
||||
def setMaxIter(value: Int): this.type = set(maxIter, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setStepSize(value: Double): this.type = set(stepSize, value)
|
||||
def setStepSize(value: Double): this.type = set(stepSize, value)
|
||||
|
||||
// Parameters from GBTClassifierParams:
|
||||
|
||||
|
|
|
|||
|
|
@ -56,27 +56,27 @@ class RandomForestClassifier @Since("1.4.0") (
|
|||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
|
||||
/**
|
||||
* Specifies how often to checkpoint the cached node IDs.
|
||||
|
|
@ -88,31 +88,31 @@ class RandomForestClassifier @Since("1.4.0") (
|
|||
* @group setParam
|
||||
*/
|
||||
@Since("1.4.0")
|
||||
override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setImpurity(value: String): this.type = set(impurity, value)
|
||||
def setImpurity(value: String): this.type = set(impurity, value)
|
||||
|
||||
// Parameters from TreeEnsembleParams:
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
|
||||
def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setSeed(value: Long): this.type = set(seed, value)
|
||||
def setSeed(value: Long): this.type = set(seed, value)
|
||||
|
||||
// Parameters from RandomForestParams:
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setNumTrees(value: Int): this.type = set(numTrees, value)
|
||||
def setNumTrees(value: Int): this.type = set(numTrees, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setFeatureSubsetStrategy(value: String): this.type =
|
||||
def setFeatureSubsetStrategy(value: String): this.type =
|
||||
set(featureSubsetStrategy, value)
|
||||
|
||||
override protected def train(dataset: Dataset[_]): RandomForestClassificationModel = {
|
||||
|
|
|
|||
|
|
@ -53,27 +53,27 @@ class DecisionTreeRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: S
|
|||
// Override parameter setters from parent trait for Java API compatibility.
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
|
||||
/**
|
||||
* Specifies how often to checkpoint the cached node IDs.
|
||||
|
|
@ -85,15 +85,15 @@ class DecisionTreeRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: S
|
|||
* @group setParam
|
||||
*/
|
||||
@Since("1.4.0")
|
||||
override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setImpurity(value: String): this.type = set(impurity, value)
|
||||
def setImpurity(value: String): this.type = set(impurity, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.6.0")
|
||||
override def setSeed(value: Long): this.type = set(seed, value)
|
||||
def setSeed(value: Long): this.type = set(seed, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("2.0.0")
|
||||
|
|
|
|||
|
|
@ -68,27 +68,27 @@ class GBTRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String)
|
|||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
|
||||
/**
|
||||
* Specifies how often to checkpoint the cached node IDs.
|
||||
|
|
@ -100,7 +100,7 @@ class GBTRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String)
|
|||
* @group setParam
|
||||
*/
|
||||
@Since("1.4.0")
|
||||
override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
|
||||
/**
|
||||
* The impurity setting is ignored for GBT models.
|
||||
|
|
@ -109,7 +109,7 @@ class GBTRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String)
|
|||
* @group setParam
|
||||
*/
|
||||
@Since("1.4.0")
|
||||
override def setImpurity(value: String): this.type = {
|
||||
def setImpurity(value: String): this.type = {
|
||||
logWarning("GBTRegressor.setImpurity should NOT be used")
|
||||
this
|
||||
}
|
||||
|
|
@ -118,21 +118,21 @@ class GBTRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String)
|
|||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
|
||||
def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setSeed(value: Long): this.type = set(seed, value)
|
||||
def setSeed(value: Long): this.type = set(seed, value)
|
||||
|
||||
// Parameters from GBTParams:
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxIter(value: Int): this.type = set(maxIter, value)
|
||||
def setMaxIter(value: Int): this.type = set(maxIter, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setStepSize(value: Double): this.type = set(stepSize, value)
|
||||
def setStepSize(value: Double): this.type = set(stepSize, value)
|
||||
|
||||
// Parameters from GBTRegressorParams:
|
||||
|
||||
|
|
|
|||
|
|
@ -55,27 +55,27 @@ class RandomForestRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: S
|
|||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
|
||||
/** @group expertSetParam */
|
||||
@Since("1.4.0")
|
||||
override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
|
||||
/**
|
||||
* Specifies how often to checkpoint the cached node IDs.
|
||||
|
|
@ -87,31 +87,31 @@ class RandomForestRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: S
|
|||
* @group setParam
|
||||
*/
|
||||
@Since("1.4.0")
|
||||
override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setImpurity(value: String): this.type = set(impurity, value)
|
||||
def setImpurity(value: String): this.type = set(impurity, value)
|
||||
|
||||
// Parameters from TreeEnsembleParams:
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
|
||||
def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setSeed(value: Long): this.type = set(seed, value)
|
||||
def setSeed(value: Long): this.type = set(seed, value)
|
||||
|
||||
// Parameters from RandomForestParams:
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setNumTrees(value: Int): this.type = set(numTrees, value)
|
||||
def setNumTrees(value: Int): this.type = set(numTrees, value)
|
||||
|
||||
/** @group setParam */
|
||||
@Since("1.4.0")
|
||||
override def setFeatureSubsetStrategy(value: String): this.type =
|
||||
def setFeatureSubsetStrategy(value: String): this.type =
|
||||
set(featureSubsetStrategy, value)
|
||||
|
||||
override protected def train(dataset: Dataset[_]): RandomForestRegressionModel = {
|
||||
|
|
|
|||
|
|
@ -109,80 +109,24 @@ private[ml] trait DecisionTreeParams extends PredictorParams
|
|||
setDefault(maxDepth -> 5, maxBins -> 32, minInstancesPerNode -> 1, minInfoGain -> 0.0,
|
||||
maxMemoryInMB -> 256, cacheNodeIds -> false, checkpointInterval -> 10)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setMaxDepth(value: Int): this.type = set(maxDepth, value)
|
||||
|
||||
/** @group getParam */
|
||||
final def getMaxDepth: Int = $(maxDepth)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setMaxBins(value: Int): this.type = set(maxBins, value)
|
||||
|
||||
/** @group getParam */
|
||||
final def getMaxBins: Int = $(maxBins)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
|
||||
|
||||
/** @group getParam */
|
||||
final def getMinInstancesPerNode: Int = $(minInstancesPerNode)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
|
||||
|
||||
/** @group getParam */
|
||||
final def getMinInfoGain: Double = $(minInfoGain)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setSeed(value: Long): this.type = set(seed, value)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group expertSetParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
|
||||
|
||||
/** @group expertGetParam */
|
||||
final def getMaxMemoryInMB: Int = $(maxMemoryInMB)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group expertSetParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
|
||||
|
||||
/** @group expertGetParam */
|
||||
final def getCacheNodeIds: Boolean = $(cacheNodeIds)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
|
||||
|
||||
/** (private[ml]) Create a Strategy instance to use with the old API. */
|
||||
private[ml] def getOldStrategy(
|
||||
categoricalFeatures: Map[Int, Int],
|
||||
|
|
@ -225,13 +169,6 @@ private[ml] trait TreeClassifierParams extends Params {
|
|||
|
||||
setDefault(impurity -> "gini")
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setImpurity(value: String): this.type = set(impurity, value)
|
||||
|
||||
/** @group getParam */
|
||||
final def getImpurity: String = $(impurity).toLowerCase(Locale.ROOT)
|
||||
|
||||
|
|
@ -276,13 +213,6 @@ private[ml] trait TreeRegressorParams extends Params {
|
|||
|
||||
setDefault(impurity -> "variance")
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setImpurity(value: String): this.type = set(impurity, value)
|
||||
|
||||
/** @group getParam */
|
||||
final def getImpurity: String = $(impurity).toLowerCase(Locale.ROOT)
|
||||
|
||||
|
|
@ -338,13 +268,6 @@ private[ml] trait TreeEnsembleParams extends DecisionTreeParams {
|
|||
|
||||
setDefault(subsamplingRate -> 1.0)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
|
||||
|
||||
/** @group getParam */
|
||||
final def getSubsamplingRate: Double = $(subsamplingRate)
|
||||
|
||||
|
|
@ -382,13 +305,6 @@ private[ml] trait RandomForestParams extends TreeEnsembleParams {
|
|||
|
||||
setDefault(numTrees -> 20)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setNumTrees(value: Int): this.type = set(numTrees, value)
|
||||
|
||||
/** @group getParam */
|
||||
final def getNumTrees: Int = $(numTrees)
|
||||
|
||||
|
|
@ -430,13 +346,6 @@ private[ml] trait RandomForestParams extends TreeEnsembleParams {
|
|||
|
||||
setDefault(featureSubsetStrategy -> "auto")
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setFeatureSubsetStrategy(value: String): this.type = set(featureSubsetStrategy, value)
|
||||
|
||||
/** @group getParam */
|
||||
final def getFeatureSubsetStrategy: String = $(featureSubsetStrategy).toLowerCase(Locale.ROOT)
|
||||
}
|
||||
|
|
@ -471,13 +380,6 @@ private[ml] trait GBTParams extends TreeEnsembleParams with HasMaxIter {
|
|||
// final val validationTol: DoubleParam = new DoubleParam(this, "validationTol", "")
|
||||
// validationTol -> 1e-5
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setMaxIter(value: Int): this.type = set(maxIter, value)
|
||||
|
||||
/**
|
||||
* Param for Step size (a.k.a. learning rate) in interval (0, 1] for shrinking
|
||||
* the contribution of each estimator.
|
||||
|
|
@ -491,13 +393,6 @@ private[ml] trait GBTParams extends TreeEnsembleParams with HasMaxIter {
|
|||
/** @group getParam */
|
||||
final def getStepSize: Double = $(stepSize)
|
||||
|
||||
/**
|
||||
* @deprecated This method is deprecated and will be removed in 2.2.0.
|
||||
* @group setParam
|
||||
*/
|
||||
@deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
|
||||
def setStepSize(value: Double): this.type = set(stepSize, value)
|
||||
|
||||
setDefault(maxIter -> 20, stepSize -> 0.1)
|
||||
|
||||
/** (private[ml]) Create a BoostingStrategy instance to use with the old API. */
|
||||
|
|
|
|||
|
|
@ -42,16 +42,6 @@ import org.apache.spark.util.Utils
|
|||
private[util] sealed trait BaseReadWrite {
|
||||
private var optionSparkSession: Option[SparkSession] = None
|
||||
|
||||
/**
|
||||
* Sets the Spark SQLContext to use for saving/loading.
|
||||
*/
|
||||
@Since("1.6.0")
|
||||
@deprecated("Use session instead, This method will be removed in 2.2.0.", "2.0.0")
|
||||
def context(sqlContext: SQLContext): this.type = {
|
||||
optionSparkSession = Option(sqlContext.sparkSession)
|
||||
this
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets the Spark Session to use for saving/loading.
|
||||
*/
|
||||
|
|
@ -130,9 +120,6 @@ abstract class MLWriter extends BaseReadWrite with Logging {
|
|||
|
||||
// override for Java compatibility
|
||||
override def session(sparkSession: SparkSession): this.type = super.session(sparkSession)
|
||||
|
||||
// override for Java compatibility
|
||||
override def context(sqlContext: SQLContext): this.type = super.session(sqlContext.sparkSession)
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
@ -188,9 +175,6 @@ abstract class MLReader[T] extends BaseReadWrite {
|
|||
|
||||
// override for Java compatibility
|
||||
override def session(sparkSession: SparkSession): this.type = super.session(sparkSession)
|
||||
|
||||
// override for Java compatibility
|
||||
override def context(sqlContext: SQLContext): this.type = super.session(sqlContext.sparkSession)
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
|
|||
|
|
@ -1005,6 +1005,74 @@ object MimaExcludes {
|
|||
ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setFeatureSubsetStrategy"),
|
||||
ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.numTrees"),
|
||||
ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setFeatureSubsetStrategy")
|
||||
) ++ Seq(
|
||||
// [SPARK-20606] ML 2.2 QA: Remove deprecated methods for ML
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setSeed"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setMinInfoGain"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setCacheNodeIds"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setCheckpointInterval"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setMaxDepth"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setImpurity"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setMaxMemoryInMB"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setMaxBins"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setMinInstancesPerNode"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setSeed"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMinInfoGain"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setSubsamplingRate"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMaxIter"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setCacheNodeIds"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setCheckpointInterval"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMaxDepth"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setImpurity"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMaxMemoryInMB"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setStepSize"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMaxBins"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMinInstancesPerNode"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setSeed"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setMinInfoGain"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setSubsamplingRate"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setCacheNodeIds"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setCheckpointInterval"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setMaxDepth"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setImpurity"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setMaxMemoryInMB"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setFeatureSubsetStrategy"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setMaxBins"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setMinInstancesPerNode"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setSeed"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setMinInfoGain"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setCacheNodeIds"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setCheckpointInterval"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setMaxDepth"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setImpurity"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setMaxMemoryInMB"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setMaxBins"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setMinInstancesPerNode"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setSeed"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMinInfoGain"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setSubsamplingRate"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMaxIter"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setCacheNodeIds"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setCheckpointInterval"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMaxDepth"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setImpurity"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMaxMemoryInMB"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setStepSize"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMaxBins"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMinInstancesPerNode"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setSeed"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setMinInfoGain"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setSubsamplingRate"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setCacheNodeIds"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setCheckpointInterval"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setMaxDepth"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setImpurity"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setMaxMemoryInMB"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setFeatureSubsetStrategy"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setMaxBins"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setMinInstancesPerNode"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.util.MLWriter.context"),
|
||||
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.util.MLReader.context")
|
||||
)
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -76,13 +76,6 @@ class MLWriter(object):
|
|||
"""Overwrites if the output path already exists."""
|
||||
raise NotImplementedError("MLWriter is not yet implemented for type: %s" % type(self))
|
||||
|
||||
def context(self, sqlContext):
|
||||
"""
|
||||
Sets the SQL context to use for saving.
|
||||
.. note:: Deprecated in 2.1 and will be removed in 2.2, use session instead.
|
||||
"""
|
||||
raise NotImplementedError("MLWriter is not yet implemented for type: %s" % type(self))
|
||||
|
||||
def session(self, sparkSession):
|
||||
"""Sets the Spark Session to use for saving."""
|
||||
raise NotImplementedError("MLWriter is not yet implemented for type: %s" % type(self))
|
||||
|
|
@ -110,15 +103,6 @@ class JavaMLWriter(MLWriter):
|
|||
self._jwrite.overwrite()
|
||||
return self
|
||||
|
||||
def context(self, sqlContext):
|
||||
"""
|
||||
Sets the SQL context to use for saving.
|
||||
.. note:: Deprecated in 2.1 and will be removed in 2.2, use session instead.
|
||||
"""
|
||||
warnings.warn("Deprecated in 2.1 and will be removed in 2.2, use session instead.")
|
||||
self._jwrite.context(sqlContext._ssql_ctx)
|
||||
return self
|
||||
|
||||
def session(self, sparkSession):
|
||||
"""Sets the Spark Session to use for saving."""
|
||||
self._jwrite.session(sparkSession._jsparkSession)
|
||||
|
|
@ -165,13 +149,6 @@ class MLReader(object):
|
|||
"""Load the ML instance from the input path."""
|
||||
raise NotImplementedError("MLReader is not yet implemented for type: %s" % type(self))
|
||||
|
||||
def context(self, sqlContext):
|
||||
"""
|
||||
Sets the SQL context to use for loading.
|
||||
.. note:: Deprecated in 2.1 and will be removed in 2.2, use session instead.
|
||||
"""
|
||||
raise NotImplementedError("MLReader is not yet implemented for type: %s" % type(self))
|
||||
|
||||
def session(self, sparkSession):
|
||||
"""Sets the Spark Session to use for loading."""
|
||||
raise NotImplementedError("MLReader is not yet implemented for type: %s" % type(self))
|
||||
|
|
@ -197,15 +174,6 @@ class JavaMLReader(MLReader):
|
|||
% self._clazz)
|
||||
return self._clazz._from_java(java_obj)
|
||||
|
||||
def context(self, sqlContext):
|
||||
"""
|
||||
Sets the SQL context to use for loading.
|
||||
.. note:: Deprecated in 2.1 and will be removed in 2.2, use session instead.
|
||||
"""
|
||||
warnings.warn("Deprecated in 2.1 and will be removed in 2.2, use session instead.")
|
||||
self._jread.context(sqlContext._ssql_ctx)
|
||||
return self
|
||||
|
||||
def session(self, sparkSession):
|
||||
"""Sets the Spark Session to use for loading."""
|
||||
self._jread.session(sparkSession._jsparkSession)
|
||||
|
|
|
|||
Loading…
Reference in a new issue