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Implement slope for Pseduo-Huber. (#7727)

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* Add objective and metric.
* Some refactoring for CPU/GPU dispatching using linalg module.
This commit is contained in:
Jiaming Yuan
2022-03-14 21:42:38 +08:00
committed by GitHub
parent 4dafb5fac8
commit 98d6faefd6
28 changed files with 456 additions and 290 deletions
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32
src/objective/regression_loss.h
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@@ -105,38 +105,6 @@ struct LogisticRegression {
static ObjInfo Info() { return {ObjInfo::kRegression, false}; }
};
struct PseudoHuberError {
XGBOOST_DEVICE static bst_float PredTransform(bst_float x) {
return x;
}
XGBOOST_DEVICE static bool CheckLabel(bst_float) {
return true;
}
XGBOOST_DEVICE static bst_float FirstOrderGradient(bst_float predt, bst_float label) {
const float z = predt - label;
const float scale_sqrt = std::sqrt(1 + std::pow(z, 2));
return z/scale_sqrt;
}
XGBOOST_DEVICE static bst_float SecondOrderGradient(bst_float predt, bst_float label) {
const float scale = 1 + std::pow(predt - label, 2);
const float scale_sqrt = std::sqrt(scale);
return 1/(scale*scale_sqrt);
}
static bst_float ProbToMargin(bst_float base_score) {
return base_score;
}
static const char* LabelErrorMsg() {
return "";
}
static const char* DefaultEvalMetric() {
return "mphe";
}
static const char* Name() {
return "reg:pseudohubererror";
}
static ObjInfo Info() { return {ObjInfo::kRegression, false}; }
};
// logistic loss for binary classification task
struct LogisticClassification : public LogisticRegression {
static const char* DefaultEvalMetric() { return "logloss"; }