Sha256: b45e4b4f1f0ee19116fc88eba64cdead36f88f07c89aba46fdbbb77b3d673ed1
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Versions: 9
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Contents
#pragma once
#include "LDA.h"
namespace tomoto
{
template<TermWeight _tw>
struct DocumentSLDA : public DocumentLDA<_tw>
{
using BaseDocument = DocumentLDA<_tw>;
using DocumentLDA<_tw>::DocumentLDA;
std::vector<Float> y;
RawDoc::MiscType makeMisc(const ITopicModel* tm) const override
{
RawDoc::MiscType ret = DocumentLDA<_tw>::makeMisc(tm);
ret["y"] = y;
return ret;
}
DEFINE_SERIALIZER_AFTER_BASE_WITH_VERSION(BaseDocument, 0, y);
DEFINE_TAGGED_SERIALIZER_AFTER_BASE_WITH_VERSION(BaseDocument, 1, 0x00010001, y);
};
struct SLDAArgs;
class ISLDAModel : public ILDAModel
{
public:
enum class GLM
{
linear = 0,
binary_logistic = 1,
};
using DefaultDocType = DocumentSLDA<TermWeight::one>;
static ISLDAModel* create(TermWeight _weight, const SLDAArgs& args,
bool scalarRng = false);
virtual size_t getF() const = 0;
virtual std::vector<Float> getRegressionCoef(size_t f) const = 0;
virtual GLM getTypeOfVar(size_t f) const = 0;
virtual std::vector<Float> estimateVars(const DocumentBase* doc) const = 0;
};
struct SLDAArgs : public LDAArgs
{
std::vector<ISLDAModel::GLM> vars;
std::vector<Float> mu;
std::vector<Float> nuSq;
std::vector<Float> glmParam;
};
}
Version data entries
9 entries across 9 versions & 1 rubygems