Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r93612915
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -397,49 +436,132 @@ object GeneralizedLinearRegression extends
DefaultParamsReadable[GeneralizedLine
/** Trim the fitted value so that it will be in valid range. */
def project(mu: Double): Double = mu
+
}
private[regression] object Family {
/**
- * Gets the [[Family]] object from its name.
+ * Gets the [[Family]] object based on family and variancePower.
+ * 1) retrieve object based on family name
+ * 2) if family name is tweedie, retrieve object based on variancePower
*
- * @param name family name: "gaussian", "binomial", "poisson" or
"gamma".
+ * @param model a GenerealizedLinearRegressionBase object
*/
- def fromName(name: String): Family = {
- name match {
- case Gaussian.name => Gaussian
- case Binomial.name => Binomial
- case Poisson.name => Poisson
- case Gamma.name => Gamma
+ def fromModel(model: GeneralizedLinearRegressionBase): Family = {
+ model.getFamily match {
+ case "gaussian" => Gaussian
+ case "binomial" => Binomial
+ case "poisson" => Poisson
+ case "gamma" => Gamma
+ case "tweedie" =>
+ model.getVariancePower match {
+ case 0.0 => Gaussian
+ case 1.0 => Poisson
+ case 2.0 => Gamma
+ case default => new TweedieFamily(default)
+ }
}
}
}
/**
- * Gaussian exponential family distribution.
- * The default link for the Gaussian family is the identity link.
- */
- private[regression] object Gaussian extends Family("gaussian") {
+ * Tweedie exponential family distribution.
+ * This includes the special cases of Gaussian, Poisson and Gamma.
+ */
+ private[regression] class TweedieFamily(private val variancePower:
Double)
+ extends Family{
+
+ val name: String = variancePower match {
+ case 0.0 => "gaussian"
+ case 1.0 => "poisson"
+ case 2.0 => "gamma"
+ case default => "tweedie"
+ }
+ /*
+ The canonical link is 1 - variancePower. Except for the special
cases of Gaussian,
+ Poisson and Gamma, the canonical link is rarely used. Set Log as the
default link.
+ */
+ val defaultLink: Link = variancePower match {
+ case 0.0 => Identity
+ case 1.0 => Log
+ case 2.0 => Inverse
+ case _ => Log
+ }
- val defaultLink: Link = Identity
+ override def initialize(y: Double, weight: Double): Double = {
+ if (variancePower >= 1.0 && variancePower < 2.0) {
+ require(y >= 0.0, s"The response variable of the specified $name
distribution " +
+ s"should be non-negative, but got $y")
+ } else if (variancePower >= 2.0) {
+ require(y > 0.0, s"The response variable of the specified $name
distribution " +
+ s"should be non-negative, but got $y")
+ }
+ if (y == 0) delta else y
+ }
- override def initialize(y: Double, weight: Double): Double = y
+ override def variance(mu: Double): Double = {
--- End diff --
Instead of case statements like this, why not just override in subclasses?
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