Options for the Python MVA method. More...

#include <Python.h>

Inheritance diagram for PythonOptions:

Collaboration diagram for PythonOptions:

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Public Member Functions
virtual void	load (const boost::property_tree::ptree &pt) override
	Load mechanism to load Options from a xml tree. More...

virtual void	save (boost::property_tree::ptree &pt) const override
	Save mechanism to store Options in a xml tree. More...

virtual po::options_description	getDescription () override
	Returns a program options description for all available options.

virtual std::string	getMethod () const override
	Return method name.

Public Attributes
std::string	m_framework = "sklearn"
	framework to use e.g. More...

std::string	m_steering_file = ""
	steering file provided by the user to override the functions in the framework

std::string	m_config = "null"
	Config string in json, which is passed to the get model function.

unsigned int	m_mini_batch_size = 0
	Mini batch size, 0 passes the whole data in one call.

unsigned int	m_nIterations = 1
	Number of iterations trough the whole data.

double	m_training_fraction = 1.0
	Fraction of data passed as training data, rest is passed as test data.

bool	m_normalize = false
	Normalize the inputs (shift mean to zero and std to 1)

Detailed Description

Options for the Python MVA method.

Definition at line 54 of file Python.h.

Member Function Documentation

void load ( const boost::property_tree::ptree & pt )

overridevirtual

Load mechanism to load Options from a xml tree.

Parameters

pt xml tree

Implements Options.

Definition at line 30 of file Python.cc.

void save ( boost::property_tree::ptree & pt ) const

overridevirtual

Save mechanism to store Options in a xml tree.

Parameters

pt xml tree

Implements Options.

Definition at line 51 of file Python.cc.

std::string m_framework = "sklearn"

framework to use e.g.

sklearn, xgboost, theano, tensorflow, ...

Definition at line 79 of file Python.h.

The documentation for this class was generated from the following files: