[ML] Fix handling of numerical precision loss in logistic loss gradient and curvature (#1041)

tveasey · web-flow · commit 854ed5d8e444 · 2020-03-06T17:55:13.000Z
diff --git a/lib/maths/CBoostedTreeLoss.cc b/lib/maths/CBoostedTreeLoss.cc
@@ -308,8 +308,9 @@ void CBinomialLogistic::gradient(const TMemoryMappedFloatVector& prediction,
                                  double weight) const {
     if (prediction(0) > -LOG_EPSILON && actual == 1.0) {
         writer(0, -weight * std::exp(-prediction(0)));
+    } else {
+        writer(0, weight * (CTools::logisticFunction(prediction(0)) - actual));
     }
-    writer(0, weight * (CTools::logisticFunction(prediction(0)) - actual));
 }
 
 void CBinomialLogistic::curvature(const TMemoryMappedFloatVector& prediction,
@@ -318,9 +319,10 @@ void CBinomialLogistic::curvature(const TMemoryMappedFloatVector& prediction,
                                   double weight) const {
     if (prediction(0) > -LOG_EPSILON) {
         writer(0, weight * std::exp(-prediction(0)));
+    } else {
+        double probability{CTools::logisticFunction(prediction(0))};
+        writer(0, weight * probability * (1.0 - probability));
     }
-    double probability{CTools::logisticFunction(prediction(0))};
-    writer(0, weight * probability * (1.0 - probability));
 }
 
 bool CBinomialLogistic::isCurvatureConstant() const {

Original file line number	Diff line number	Diff line change
`@@ -308,8 +308,9 @@ void CBinomialLogistic::gradient(const TMemoryMappedFloatVector& prediction,`
`308`	`308`	`double weight) const {`
`309`	`309`	`if (prediction(0) > -LOG_EPSILON && actual == 1.0) {`
`310`	`310`	`writer(0, -weight * std::exp(-prediction(0)));`
	`311`	`+ } else {`
	`312`	`+ writer(0, weight * (CTools::logisticFunction(prediction(0)) - actual));`
`311`	`313`	`}`
`312`		`- writer(0, weight * (CTools::logisticFunction(prediction(0)) - actual));`
`313`	`314`	`}`
`314`	`315`
`315`	`316`	`void CBinomialLogistic::curvature(const TMemoryMappedFloatVector& prediction,`
`@@ -318,9 +319,10 @@ void CBinomialLogistic::curvature(const TMemoryMappedFloatVector& prediction,`
`318`	`319`	`double weight) const {`
`319`	`320`	`if (prediction(0) > -LOG_EPSILON) {`
`320`	`321`	`writer(0, weight * std::exp(-prediction(0)));`
	`322`	`+ } else {`
	`323`	`+ double probability{CTools::logisticFunction(prediction(0))};`
	`324`	`+ writer(0, weight * probability * (1.0 - probability));`
`321`	`325`	`}`
`322`		`- double probability{CTools::logisticFunction(prediction(0))};`
`323`		`- writer(0, weight * probability * (1.0 - probability));`
`324`	`326`	`}`
`325`	`327`
`326`	`328`	`bool CBinomialLogistic::isCurvatureConstant() const {`