Sha256: f19b37d45c4613b0e36a89db6c0e7a07a0fdd09817d24d4131179c64a5afaf4b
Contents?: true
Size: 1.42 KB
Versions: 5
Compression:
Stored size: 1.42 KB
Contents
#pragma once
#include "DMR.h"
namespace tomoto
{
template<TermWeight _tw>
struct DocumentGDMR : public DocumentDMR<_tw>
{
using BaseDocument = DocumentDMR<_tw>;
using DocumentDMR<_tw>::DocumentDMR;
std::vector<Float> metadataOrg, metadataNormalized;
DEFINE_SERIALIZER_AFTER_BASE_WITH_VERSION(BaseDocument, 0, metadataOrg);
DEFINE_TAGGED_SERIALIZER_AFTER_BASE_WITH_VERSION(BaseDocument, 1, 0x00010001, metadataOrg, metadataNormalized);
};
class IGDMRModel : public IDMRModel
{
public:
using DefaultDocType = DocumentDMR<TermWeight::one>;
static IGDMRModel* create(TermWeight _weight, size_t _K = 1, const std::vector<uint64_t>& _degreeByF = {},
Float defaultAlpha = 1.0, Float _sigma = 1.0, Float _sigma0 = 1.0, Float _eta = 0.01, Float _alphaEps = 1e-10,
size_t seed = std::random_device{}(),
bool scalarRng = false);
virtual Float getSigma0() const = 0;
virtual void setSigma0(Float) = 0;
virtual const std::vector<uint64_t>& getFs() const = 0;
virtual std::vector<Float> getLambdaByTopic(Tid tid) const = 0;
virtual std::vector<Float> getTDF(const Float* metadata, bool normalize) const = 0;
virtual std::vector<Float> getTDFBatch(const Float* metadata, size_t stride, size_t cnt, bool normalize) const = 0;
virtual void setMdRange(const std::vector<Float>& vMin, const std::vector<Float>& vMax) = 0;
virtual void getMdRange(std::vector<Float>& vMin, std::vector<Float>& vMax) const = 0;
};
}
Version data entries
5 entries across 5 versions & 1 rubygems