Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/17715#discussion_r114031122
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -178,11 +178,86 @@ private[classification] trait
LogisticRegressionParams extends ProbabilisticClas
}
}
+ /**
+ * The lower bounds on coefficients if fitting under bound constrained
optimization.
+ * 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.
+ *
+ * @group param
+ */
+ @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 */
+ @Since("2.2.0")
+ def getLowerBoundsOnCoefficients: Matrix = $(lowerBoundsOnCoefficients)
+
+ /**
+ * The upper bounds on coefficients if fitting under bound constrained
optimization.
+ * 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.
+ *
+ * @group param
+ */
+ @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 */
+ @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.
+ *
+ * @group param
+ */
+ @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 */
+ @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.
+ *
+ * @group param
+ */
+ @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 */
+ @Since("2.2.0")
+ def getUpperBoundsOnIntercepts: Vector = $(upperBoundsOnIntercepts)
+
+ protected def usingBoundConstrainedOptimization: Boolean = {
+ isSet(lowerBoundsOnCoefficients) || isSet(upperBoundsOnCoefficients) ||
+ isSet(lowerBoundsOnIntercepts) || isSet(upperBoundsOnIntercepts)
+ }
+
override protected def validateAndTransformSchema(
schema: StructType,
fitting: Boolean,
featuresDataType: DataType): StructType = {
checkThresholdConsistency()
+ if (usingBoundConstrainedOptimization) {
+ require($(elasticNetParam) == 0.0, "Fitting under bound constrained
optimization only " +
+ s"supports L2 regularization, but got elasticNetParam =
$getElasticNetParam.")
+ }
+ if (!$(fitIntercept)) {
+ require(!isSet(lowerBoundsOnIntercepts) &&
!isSet(upperBoundsOnIntercepts),
+ "Pls don't set bounds on intercepts if fitting without intercept.")
--- End diff --
"Pls don't" --> "Please do not"
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