Options for the Python MVA method.
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#include <Python.h>
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virtual void | load (const boost::property_tree::ptree &pt) override |
| Load mechanism to load Options from a xml tree. More...
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virtual void | save (boost::property_tree::ptree &pt) const override |
| Save mechanism to store Options in a xml tree. More...
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virtual po::options_description | getDescription () override |
| Returns a program options description for all available options.
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virtual std::string | getMethod () const override |
| Return method name.
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std::string | m_framework = "sklearn" |
| framework to use e.g. More...
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std::string | m_steering_file = "" |
| steering file provided by the user to override the functions in the framework
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std::string | m_config = "null" |
| Config string in json, which is passed to the get model function.
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unsigned int | m_mini_batch_size = 0 |
| Mini batch size, 0 passes the whole data in one call.
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unsigned int | m_nIterations = 1 |
| Number of iterations through the whole data.
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double | m_training_fraction = 1.0 |
| Fraction of data passed as training data, rest is passed as test data.
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bool | m_normalize = false |
| Normalize the inputs (shift mean to zero and std to 1)
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Options for the Python MVA method.
Definition at line 52 of file Python.h.
◆ load()
void load |
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const boost::property_tree::ptree & |
pt | ) |
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overridevirtual |
Load mechanism to load Options from a xml tree.
- Parameters
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Implements Options.
Definition at line 30 of file Python.cc.
32 int version = pt.get<
int>(
"Python_version");
33 if (version < 1 or version > 2) {
34 B2ERROR(
"Unknown weightfile version " << std::to_string(version));
35 throw std::runtime_error(
"Unknown weightfile version " + std::to_string(version));
37 m_framework = pt.get<std::string>(
"Python_framework");
41 m_config = pt.get<std::string>(
"Python_config");
unsigned int m_nIterations
Number of iterations through the whole data.
std::string m_steering_file
steering file provided by the user to override the functions in the framework
std::string m_framework
framework to use e.g.
std::string m_config
Config string in json, which is passed to the get model function.
bool m_normalize
Normalize the inputs (shift mean to zero and std to 1)
double m_training_fraction
Fraction of data passed as training data, rest is passed as test data.
unsigned int m_mini_batch_size
Mini batch size, 0 passes the whole data in one call.
◆ save()
void save |
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boost::property_tree::ptree & |
pt | ) |
const |
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overridevirtual |
◆ m_framework
std::string m_framework = "sklearn" |
framework to use e.g.
sklearn, xgboost, theano, tensorflow, ...
Definition at line 77 of file Python.h.
The documentation for this class was generated from the following files: