#include <modelSet.h>
Public Member Functions | |
modelSet () | |
virtual | ~modelSet () |
virtual bool | train (const std::vector< trainingExample > &trainingSet) |
bool | initialize () |
std::vector< double > | process (const std::vector< double > &inputVector) |
std::string | getJSON () |
void | writeJSON (const std::string &filepath) |
bool | putJSON (const std::string &jsonMessage) |
bool | readJSON (const std::string &filepath) |
Protected Attributes | |
std::vector< baseModel * > | myModelSet |
int | numInputs |
std::vector< std::string > | inputNames |
int | numOutputs |
bool | created |
This class holds a set of models with the same or different algorithms.
modelSet::modelSet | ( | ) |
No arguments, don't create any models yet
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virtual |
std::string modelSet::getJSON | ( | ) |
Get a JSON representation of the model in the form of a styled string
bool modelSet::initialize | ( | ) |
reset to pre-training state
std::vector< double > modelSet::process | ( | const std::vector< double > & | inputVector | ) |
run regression or classification for each model
bool modelSet::putJSON | ( | const std::string & | jsonMessage | ) |
configure empty model with string. See getJSON()
bool modelSet::readJSON | ( | const std::string & | filepath | ) |
read a JSON file at file path and build a modelSet from it
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virtual |
Train on a specified set, causes creation if not created
Reimplemented in classification, and regression.
void modelSet::writeJSON | ( | const std::string & | filepath | ) |
Write a JSON model description to specified file path
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