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[Spark-24024][ML] Fix poisson deviance calculations in GLM to handle y = 0 #21125

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[Spark-24024][ML] Fix poisson deviance calculations in GLM to handle y = 0 #21125

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3c6a4da
fix deviance calculation when y = 0
tengpeng Apr 23, 2018
da53b1a
Address comments
tengpeng Apr 23, 2018
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10 changes: 5 additions & 5 deletions mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -471,6 +471,10 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine

private[regression] val epsilon: Double = 1E-16

private[regression] def ylogy(y: Double, mu: Double): Double = {
if (y == 0) 0.0 else y * math.log(y / mu)
}

/**
* Wrapper of family and link combination used in the model.
*/
Expand Down Expand Up @@ -725,10 +729,6 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine

override def variance(mu: Double): Double = mu * (1.0 - mu)

private def ylogy(y: Double, mu: Double): Double = {
if (y == 0) 0.0 else y * math.log(y / mu)
}

override def deviance(y: Double, mu: Double, weight: Double): Double = {
2.0 * weight * (ylogy(y, mu) + ylogy(1.0 - y, 1.0 - mu))
}
Expand Down Expand Up @@ -783,7 +783,7 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine
override def variance(mu: Double): Double = mu

override def deviance(y: Double, mu: Double, weight: Double): Double = {
2.0 * weight * (y * math.log(y / mu) - (y - mu))
2.0 * weight * (ylogy(y, mu) - (y - mu))
}

override def aic(
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10 changes: 10 additions & 0 deletions mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
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Expand Up @@ -493,11 +493,20 @@ class GeneralizedLinearRegressionSuite extends MLTest with DefaultReadWriteTest
}
[1] -0.0457441 -0.6833928
[1] 1.8121235 -0.1747493 -0.5815417
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Can you update the R script which generate the deviance?

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Updated. The updated script is sufficient to calculate deviance on its own.


R code for deivance calculation:
data = cbind(y=c(0,1,0,0,0,1), x1=c(18, 12, 15, 13, 15, 16), x2=c(1,0,0,2,1,1))
summary(glm(y~x1+x2, family=poisson, data=data.frame(data)))$deviance
[1] 3.70055
summary(glm(y~x1+x2-1, family=poisson, data=data.frame(data)))$deviance
[1] 3.809296
*/
val expected = Seq(
Vectors.dense(0.0, -0.0457441, -0.6833928),
Vectors.dense(1.8121235, -0.1747493, -0.5815417))

val residualDeviancesR = Array(3.809296, 3.70055)

import GeneralizedLinearRegression._

var idx = 0
Expand All @@ -510,6 +519,7 @@ class GeneralizedLinearRegressionSuite extends MLTest with DefaultReadWriteTest
val actual = Vectors.dense(model.intercept, model.coefficients(0), model.coefficients(1))
assert(actual ~= expected(idx) absTol 1e-4, "Model mismatch: GLM with poisson family, " +
s"$link link and fitIntercept = $fitIntercept (with zero values).")
assert(model.summary.deviance ~== residualDeviancesR(idx) absTol 1E-3)
idx += 1
}
}
Expand Down