Github user actuaryzhang commented on a diff in the pull request: https://github.com/apache/spark/pull/16149#discussion_r91246870 --- Diff: mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala --- @@ -479,7 +479,12 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine numInstances: Double, weightSum: Double): Double = { -2.0 * predictions.map { case (y: Double, mu: Double, weight: Double) => - weight * dist.Binomial(1, mu).logProbabilityOf(math.round(y).toInt) + val wt = math.round(weight).toInt + if (wt == 0) { + 0.0 + } else { + dist.Binomial(wt, mu).logProbabilityOf(math.round(y * weight).toInt) --- End diff -- @srowen The current uses [breeze](https://github.com/scalanlp/breeze/blob/master/math/src/main/scala/breeze/stats/distributions/Binomial.scala) for computing the Binomial density, which does not allow 0 trials. `require(n > 0, "n must be positive!")`. That is why I have to handle the case of `wt = 0`
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