Function OutputModel

catboost/libs/model/model_export/pmml_helpers.cpp:698–739

    namespace NPmml {

    void OutputModel(
        const TFullModel& model,
        const TString& modelFile,
        const NJson::TJsonValue& userParameters,
        const THashMap<ui32, TString>* catFeaturesHashToString) {

        CB_ENSURE(
            SafeIntegerCast<size_t>(
                CountIf(
                    model.ModelTrees->GetCatFeatures(),
                    [](const TCatFeature& catFeature) { return catFeature.UsedInModel(); }))
                == model.ModelTrees->GetOneHotFeatures().size(),
            "PMML export requires that all categorical features in the model are one hot encoded");

        CB_ENSURE(
            model.GetDimensionsCount() == 1,
            "PMML export currently supports only single-dimensional models");

        CB_ENSURE_INTERNAL(
            !model.ModelTrees->GetOneHotFeatures().size() || catFeaturesHashToString,
            "catFeaturesHashToString has to be specified if the model contains one hot features");

        // assumed regression by default

        bool isClassification = false;
        const TString lossFunctionName = model.GetLossFunctionName();
        if (lossFunctionName) {
            isClassification = IsClassificationObjective(lossFunctionName);
        }

        TOFStream out(modelFile);
        TXmlOutputContext xmlOut(&out, "PMML");
        xmlOut.AddAttr("version", "4.3")
            .AddAttr("xmlns", "http://www.dmg.org/PMML-4_3")
            .AddAttr("xmlns:xsi", "http://www.w3.org/2001/XMLSchema-instance");

        OutputHeader(model, userParameters, &xmlOut);

        OutputDataDictionary(model, isClassification, &xmlOut);

        OutputMiningModel(model, isClassification, catFeaturesHashToString, &xmlOut);
    }

    }
}