change metric for categorical sorting to match LightGBM

interpretml · Dec 24, 2024 · 5962f83 · 5962f83
1 parent 745c561
commit 5962f83
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Showing 3 changed files with 17 additions and 22 deletions.
diff --git a/python/interpret-core/tests/glassbox/ebm/test_ebm.py b/python/interpret-core/tests/glassbox/ebm/test_ebm.py
@@ -655,8 +655,13 @@ def test_eval_terms_multiclass():
 
 
 def test_ebm_sample_weight():
+    from interpret.develop import get_option, set_option
+
     X, y, names, types = make_synthetic(classes=2, output_type="float")
 
+    cat_smooth = get_option("cat_smooth")
+    set_option("cat_smooth", 2.2250738585072014e-308)
+
     ebm = ExplainableBoostingClassifier(names, types)
     ebm.fit(X, y)
 
@@ -672,6 +677,9 @@ def test_ebm_sample_weight():
     changed = ExplainableBoostingClassifier(names, types)
     changed.fit(X, y, sample_weight=weights)
 
+    # restore cat_smooth value
+    set_option("cat_smooth", cat_smooth)
+
     assert not np.array_equal(ebm.predict_proba(X), changed.predict_proba(X))
 
 

diff --git a/shared/libebm/PartitionOneDimensionalBoosting.cpp b/shared/libebm/PartitionOneDimensionalBoosting.cpp
@@ -704,19 +704,12 @@ template<bool bHessian> class CompareNodeGain final {
 
 template<bool bHessian, size_t cCompilerScores> class CompareBin final {
    bool m_bHessianRuntime;
-   FloatCalc m_regAlpha;
-   FloatCalc m_regLambda;
-   FloatCalc m_deltaStepMax;
+   FloatCalc m_categoricalSmoothing;
 
  public:
-   INLINE_ALWAYS CompareBin(const bool bHessianRuntime,
-         const FloatCalc regAlpha,
-         const FloatCalc regLambda,
-         const FloatCalc deltaStepMax) {
+   INLINE_ALWAYS CompareBin(const bool bHessianRuntime, FloatCalc categoricalSmoothing) {
       m_bHessianRuntime = bHessianRuntime;
-      m_regAlpha = regAlpha;
-      m_regLambda = regLambda;
-      m_deltaStepMax = deltaStepMax;
+      m_categoricalSmoothing = categoricalSmoothing;
    }
 
    INLINE_ALWAYS bool operator()(
@@ -729,19 +722,13 @@ template<bool bHessian, size_t cCompilerScores> class CompareBin final {
 
       const FloatCalc hess1 =
             static_cast<FloatCalc>(bUpdateWithHessian ? lhs->GetGradientPairs()[0].GetHess() : lhs->GetWeight());
-      const FloatCalc val1 = CalcNegUpdate<true>(static_cast<FloatCalc>(lhs->GetGradientPairs()[0].m_sumGradients),
-            hess1,
-            m_regAlpha,
-            m_regLambda,
-            m_deltaStepMax);
+      const FloatCalc val1 =
+            static_cast<FloatCalc>(lhs->GetGradientPairs()[0].m_sumGradients) / (hess1 + m_categoricalSmoothing);
 
       const FloatCalc hess2 =
             static_cast<FloatCalc>(bUpdateWithHessian ? rhs->GetGradientPairs()[0].GetHess() : rhs->GetWeight());
-      const FloatCalc val2 = CalcNegUpdate<true>(static_cast<FloatCalc>(rhs->GetGradientPairs()[0].m_sumGradients),
-            hess2,
-            m_regAlpha,
-            m_regLambda,
-            m_deltaStepMax);
+      const FloatCalc val2 =
+            static_cast<FloatCalc>(rhs->GetGradientPairs()[0].m_sumGradients) / (hess2 + m_categoricalSmoothing);
 
       if(val1 == val2) {
          return lhs < rhs;
@@ -835,7 +822,7 @@ template<bool bHessian, size_t cCompilerScores> class PartitionOneDimensionalBoo
          std::sort(apBins,
                ppBinsEnd,
                CompareBin<bHessian, cCompilerScores>(
-                     !(TermBoostFlags_DisableNewtonUpdate & flags), regAlpha, regLambda, deltaStepMax));
+                     !(TermBoostFlags_DisableNewtonUpdate & flags), categoricalSmoothing));
       }
 
       pRootTreeNode->BEFORE_SetBinFirst(apBins);

diff --git a/shared/libebm/tests/boosting_unusual_inputs.cpp b/shared/libebm/tests/boosting_unusual_inputs.cpp
@@ -2175,7 +2175,7 @@ static double RandomizedTesting(const AccelerationFlags acceleration) {
 }
 
 TEST_CASE("stress test, boosting") {
-   const double expected = 26838942758406.215;
+   const double expected = 26758407585917.129;
 
    double validationMetricExact = RandomizedTesting(AccelerationFlags_NONE);
    CHECK(validationMetricExact == expected);