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ability to specify threshold for the error metric

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This commit is contained in:
Vadim Khotilovich 2016-04-25 01:29:04 -05:00
parent b3c9e6a0db
commit 1160d0bf25
1 changed files with 26 additions and 10 deletions
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36
src/metric/elementwise_metric.cc
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@ -33,7 +33,7 @@ struct EvalEWiseBase : public Metric {
#pragma omp parallel for reduction(+: sum, wsum) schedule(static)
for (omp_ulong i = 0; i < ndata; ++i) {
const float wt = info.GetWeight(i);
sum += Derived::EvalRow(info.labels[i], preds[i]) * wt;
sum += static_cast<const Derived*>(this)->EvalRow(info.labels[i], preds[i]) * wt;
wsum += wt;
}
double dat[2]; dat[0] = sum, dat[1] = wsum;
@ -48,7 +48,7 @@ struct EvalEWiseBase : public Metric {
* \param label label of current instance
* \param pred prediction value of current instance
*/
inline static float EvalRow(float label, float pred);
inline float EvalRow(float label, float pred) const;
/*!
* \brief to be overridden by subclass, final transformation
* \param esum the sum statistics returned by EvalRow
@ -63,7 +63,7 @@ struct EvalRMSE : public EvalEWiseBase<EvalRMSE> {
const char *Name() const override {
return "rmse";
}
inline static float EvalRow(float label, float pred) {
inline float EvalRow(float label, float pred) const {
float diff = label - pred;
return diff * diff;
}
@ -76,7 +76,7 @@ struct EvalMAE : public EvalEWiseBase<EvalMAE> {
const char *Name() const override {
return "mae";
}
inline static float EvalRow(float label, float pred) {
inline float EvalRow(float label, float pred) const {
return std::abs(label - pred);
}
};
@ -85,7 +85,7 @@ struct EvalLogLoss : public EvalEWiseBase<EvalLogLoss> {
const char *Name() const override {
return "logloss";
}
inline static float EvalRow(float y, float py) {
inline float EvalRow(float y, float py) const {
const float eps = 1e-16f;
const float pneg = 1.0f - py;
if (py < eps) {
@ -99,20 +99,36 @@ struct EvalLogLoss : public EvalEWiseBase<EvalLogLoss> {
};
struct EvalError : public EvalEWiseBase<EvalError> {
explicit EvalError(const char* param) {
if (param != nullptr) {
std::ostringstream os;
os << "error";
CHECK_EQ(sscanf(param, "%f", &threshold_), 1)
<< "unable to parse the threshold value for the error metric";
if (threshold_ != 0.5f) os << '@' << threshold_;
name_ = os.str();
} else {
threshold_ = 0.5f;
name_ = "error";
}
}
const char *Name() const override {
return "error";
return name_.c_str();
}
inline static float EvalRow(float label, float pred) {
inline float EvalRow(float label, float pred) const {
// assume label is in [0,1]
return pred > 0.5f ? 1.0f - label : label;
return pred > threshold_ ? 1.0f - label : label;
}
protected:
float threshold_;
std::string name_;
};
struct EvalPoissionNegLogLik : public EvalEWiseBase<EvalPoissionNegLogLik> {
const char *Name() const override {
return "poisson-nloglik";
}
inline static float EvalRow(float y, float py) {
inline float EvalRow(float y, float py) const {
const float eps = 1e-16f;
if (py < eps) py = eps;
return common::LogGamma(y + 1.0f) + py - std::log(py) * y;
@ -133,7 +149,7 @@ XGBOOST_REGISTER_METRIC(LogLoss, "logloss")
XGBOOST_REGISTER_METRIC(Error, "error")
.describe("Binary classification error.")
.set_body([](const char* param) { return new EvalError(); });
.set_body([](const char* param) { return new EvalError(param); });
XGBOOST_REGISTER_METRIC(PossionNegLoglik, "poisson-nloglik")
.describe("Negative loglikelihood for poisson regression.")