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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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fix deviance calculation when y = 0
tengpeng Apr 23, 2018
da53b1a
Address comments
tengpeng Apr 23, 2018
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fix deviance calculation when y = 0
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@tengpeng
tengpeng committed Apr 23, 2018
commit 3c6a4dab973851e385b6c9a2c77e5684ad6171a4
6 changes: 5 additions & 1 deletion mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
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Expand Up @@ -782,8 +782,12 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine

override def variance(mu: Double): Double = mu

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

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@dbtsai dbtsai Apr 23, 2018

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Another ylogy implementation in Binomial. Can you move this code to object GeneralizedLinearRegression and make it private to this package?

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@tengpeng tengpeng Apr 23, 2018

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Thanks so much for the quick review. I have moved the ylog implementation to object GeneralizedLinearRegression. One quick question here: I am not sure I have fully understood why this is the right place for ylog? Thanks!

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@dbtsai dbtsai Apr 23, 2018

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Any suggestion to avoid the duplicated code? Let's followup this later if you have an idea.

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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7 changes: 4 additions & 3 deletions mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
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Expand Up @@ -495,8 +495,8 @@ class GeneralizedLinearRegressionSuite extends MLTest with DefaultReadWriteTest
[1] 1.8121235 -0.1747493 -0.5815417
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@dbtsai dbtsai Apr 23, 2018

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Can you update the R script which generate the deviance?

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@tengpeng tengpeng Apr 23, 2018

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

*/
val expected = Seq(
Vectors.dense(0.0, -0.0457441, -0.6833928),
Vectors.dense(1.8121235, -0.1747493, -0.5815417))
Vectors.dense(0.0, -0.0457441, -0.6833928, 3.8093),
Vectors.dense(1.8121235, -0.1747493, -0.5815417, 3.7006))

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@dbtsai dbtsai Apr 23, 2018

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Adding them to expected is not consistent to the rest of the test code.

How about

val residualDeviancesR = Array(3.8093, 3.7006)

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@tengpeng tengpeng Apr 23, 2018

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Modified. Thanks!

import GeneralizedLinearRegression._

Expand All @@ -507,7 +507,8 @@ class GeneralizedLinearRegressionSuite extends MLTest with DefaultReadWriteTest
val trainer = new GeneralizedLinearRegression().setFamily("poisson").setLink(link)
.setFitIntercept(fitIntercept).setLinkPredictionCol("linkPrediction")
val model = trainer.fit(dataset)
val actual = Vectors.dense(model.intercept, model.coefficients(0), model.coefficients(1))
val actual = Vectors.dense(model.intercept, model.coefficients(0), model.coefficients(1),
model.summary.deviance)
assert(actual ~= expected(idx) absTol 1e-4, "Model mismatch: GLM with poisson family, " +
s"$link link and fitIntercept = $fitIntercept (with zero values).")
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@dbtsai dbtsai Apr 23, 2018

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assert(model.summary.deviance ~== residualDeviancesR(idx) absTol 1E-3)

idx += 1
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