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[SPARK-20047][FOLLOWUP][ML] Constrained Logistic Regression follow up #17829

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[SPARK-20047][FOLLOWUP][ML] Constrained Logistic Regression follow up #17829

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54 changes: 35 additions & 19 deletions mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -183,14 +183,15 @@ private[classification] trait LogisticRegressionParams extends ProbabilisticClas
* The bound matrix must be compatible with the shape (1, number of features) for binomial
* regression, or (number of classes, number of features) for multinomial regression.
* Otherwise, it throws exception.
* Default is none.
*
* @group param
* @group expertParam
*/
@Since("2.2.0")
val lowerBoundsOnCoefficients: Param[Matrix] = new Param(this, "lowerBoundsOnCoefficients",
"The lower bounds on coefficients if fitting under bound constrained optimization.")

/** @group getParam */
/** @group expertGetParam */
@Since("2.2.0")
def getLowerBoundsOnCoefficients: Matrix = $(lowerBoundsOnCoefficients)

Expand All @@ -199,44 +200,47 @@ private[classification] trait LogisticRegressionParams extends ProbabilisticClas
* The bound matrix must be compatible with the shape (1, number of features) for binomial
* regression, or (number of classes, number of features) for multinomial regression.
* Otherwise, it throws exception.
* Default is none.
*
* @group param
* @group expertParam
*/
@Since("2.2.0")
val upperBoundsOnCoefficients: Param[Matrix] = new Param(this, "upperBoundsOnCoefficients",
"The upper bounds on coefficients if fitting under bound constrained optimization.")

/** @group getParam */
/** @group expertGetParam */
@Since("2.2.0")
def getUpperBoundsOnCoefficients: Matrix = $(upperBoundsOnCoefficients)

/**
* The lower bounds on intercepts if fitting under bound constrained optimization.
* The bounds vector size must be equal with 1 for binomial regression, or the number
* of classes for multinomial regression. Otherwise, it throws exception.
* Default is none.
*
* @group param
* @group expertParam
*/
@Since("2.2.0")
val lowerBoundsOnIntercepts: Param[Vector] = new Param(this, "lowerBoundsOnIntercepts",
"The lower bounds on intercepts if fitting under bound constrained optimization.")

/** @group getParam */
/** @group expertGetParam */
@Since("2.2.0")
def getLowerBoundsOnIntercepts: Vector = $(lowerBoundsOnIntercepts)

/**
* The upper bounds on intercepts if fitting under bound constrained optimization.
* The bound vector size must be equal with 1 for binomial regression, or the number
* of classes for multinomial regression. Otherwise, it throws exception.
* Default is none.
*
* @group param
* @group expertParam
*/
@Since("2.2.0")
val upperBoundsOnIntercepts: Param[Vector] = new Param(this, "upperBoundsOnIntercepts",
"The upper bounds on intercepts if fitting under bound constrained optimization.")

/** @group getParam */
/** @group expertGetParam */
@Since("2.2.0")
def getUpperBoundsOnIntercepts: Vector = $(upperBoundsOnIntercepts)

Expand All @@ -256,7 +260,7 @@ private[classification] trait LogisticRegressionParams extends ProbabilisticClas
}
if (!$(fitIntercept)) {
require(!isSet(lowerBoundsOnIntercepts) && !isSet(upperBoundsOnIntercepts),
"Pls don't set bounds on intercepts if fitting without intercept.")
"Please don't set bounds on intercepts if fitting without intercept.")
}
super.validateAndTransformSchema(schema, fitting, featuresDataType)
}
Expand Down Expand Up @@ -393,31 +397,31 @@ class LogisticRegression @Since("1.2.0") (
/**
* Set the lower bounds on coefficients if fitting under bound constrained optimization.
*
* @group setParam
* @group expertSetParam
*/
@Since("2.2.0")
def setLowerBoundsOnCoefficients(value: Matrix): this.type = set(lowerBoundsOnCoefficients, value)

/**
* Set the upper bounds on coefficients if fitting under bound constrained optimization.
*
* @group setParam
* @group expertSetParam
*/
@Since("2.2.0")
def setUpperBoundsOnCoefficients(value: Matrix): this.type = set(upperBoundsOnCoefficients, value)

/**
* Set the lower bounds on intercepts if fitting under bound constrained optimization.
*
* @group setParam
* @group expertSetParam
*/
@Since("2.2.0")
def setLowerBoundsOnIntercepts(value: Vector): this.type = set(lowerBoundsOnIntercepts, value)

/**
* Set the upper bounds on intercepts if fitting under bound constrained optimization.
*
* @group setParam
* @group expertSetParam
*/
@Since("2.2.0")
def setUpperBoundsOnIntercepts(value: Vector): this.type = set(upperBoundsOnIntercepts, value)
Expand All @@ -427,28 +431,40 @@ class LogisticRegression @Since("1.2.0") (
numFeatures: Int): Unit = {
if (isSet(lowerBoundsOnCoefficients)) {
require($(lowerBoundsOnCoefficients).numRows == numCoefficientSets &&
$(lowerBoundsOnCoefficients).numCols == numFeatures)
$(lowerBoundsOnCoefficients).numCols == numFeatures,
"The shape of LowerBoundsOnCoefficients must be compatible with (1, number of features) " +
"for binomial regression, or (number of classes, number of features) for multinomial " +
"regression, but found: " +
s"(${getLowerBoundsOnCoefficients.numRows}, ${getLowerBoundsOnCoefficients.numCols}).")
}
if (isSet(upperBoundsOnCoefficients)) {
require($(upperBoundsOnCoefficients).numRows == numCoefficientSets &&
$(upperBoundsOnCoefficients).numCols == numFeatures)
$(upperBoundsOnCoefficients).numCols == numFeatures,
"The shape of upperBoundsOnCoefficients must be compatible with (1, number of features) " +
"for binomial regression, or (number of classes, number of features) for multinomial " +
"regression, but found: " +
s"(${getUpperBoundsOnCoefficients.numRows}, ${getUpperBoundsOnCoefficients.numCols}).")
}
if (isSet(lowerBoundsOnIntercepts)) {
require($(lowerBoundsOnIntercepts).size == numCoefficientSets)
require($(lowerBoundsOnIntercepts).size == numCoefficientSets, "The size of " +
"lowerBoundsOnIntercepts must be equal with 1 for binomial regression, or the number of " +
s"classes for multinomial regression, but found: ${getLowerBoundsOnIntercepts.size}.")
}
if (isSet(upperBoundsOnIntercepts)) {
require($(upperBoundsOnIntercepts).size == numCoefficientSets)
require($(upperBoundsOnIntercepts).size == numCoefficientSets, "The size of " +
"upperBoundsOnIntercepts must be equal with 1 for binomial regression, or the number of " +
s"classes for multinomial regression, but found: ${getUpperBoundsOnIntercepts.size}.")
}
if (isSet(lowerBoundsOnCoefficients) && isSet(upperBoundsOnCoefficients)) {
require($(lowerBoundsOnCoefficients).toArray.zip($(upperBoundsOnCoefficients).toArray)
.forall(x => x._1 <= x._2), "LowerBoundsOnCoefficients should always " +
.forall(x => x._1 <= x._2), "LowerBoundsOnCoefficients should always be " +
"less than or equal to upperBoundsOnCoefficients, but found: " +
s"lowerBoundsOnCoefficients = $getLowerBoundsOnCoefficients, " +
s"upperBoundsOnCoefficients = $getUpperBoundsOnCoefficients.")
}
if (isSet(lowerBoundsOnIntercepts) && isSet(upperBoundsOnIntercepts)) {
require($(lowerBoundsOnIntercepts).toArray.zip($(upperBoundsOnIntercepts).toArray)
.forall(x => x._1 <= x._2), "LowerBoundsOnIntercepts should always " +
.forall(x => x._1 <= x._2), "LowerBoundsOnIntercepts should always be " +
"less than or equal to upperBoundsOnIntercepts, but found: " +
s"lowerBoundsOnIntercepts = $getLowerBoundsOnIntercepts, " +
s"upperBoundsOnIntercepts = $getUpperBoundsOnIntercepts.")
Expand Down