core_analytics\regressor Interface Reference

Regressors interface. More...

Inheritance diagram for core_analytics\regressor:

Public Member Functions
	clear_model ($uniqueid, $modelversionoutputdir)
	Delete all stored information of the current model id.
	delete_output_dir ($modeloutputdir, $uniqueid)
	Delete the output directory.
	estimate ($uniqueid, stored_file $dataset, $outputdir)
	Estimates linear values for the provided dataset samples.
	evaluate_regression ($uniqueid, $maxdeviation, $niterations, stored_file $dataset, $outputdir, $trainedmodeldir)
	Evaluates this processor regression model using the provided supervised learning dataset.
	is_ready ()
	Is it ready to predict?
	train_regression ($uniqueid, stored_file $dataset, $outputdir)
	Train this processor regression model using the provided supervised learning dataset.

Detailed Description

Regressors interface.

Copyright

2016 David Monllao

License

http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later

Member Function Documentation

clear_model()

core_analytics\predictor::clear_model ( $uniqueid, $modelversionoutputdir )

inherited

Delete all stored information of the current model id.

This method is called when there are important changes to a model, all previous training algorithms using that version of the model should be deleted.

In case you want to perform extra security measures before deleting a directory you can check that $modelversionoutputdir subdirectories can only be named 'execution', 'evaluation' or 'testing'.

Parameters

string	$uniqueid	The site model unique id string
string	$modelversionoutputdir	The output dir of this model version

Return values

null

Implemented in mlbackend_php\processor, and mlbackend_python\processor.

delete_output_dir()

core_analytics\predictor::delete_output_dir ( $modeloutputdir, $uniqueid )

inherited

Delete the output directory.

This method is called when a model is completely deleted.

In case you want to perform extra security measures before deleting a directory you can check that the subdirectories are timestamps (the model version) and each of this subdirectories' subdirectories can only be named 'execution', 'evaluation' or 'testing'.

Parameters

string	$modeloutputdir	The model directory id (parent of all model versions subdirectories).
string	$uniqueid

Return values

null

Implemented in mlbackend_php\processor, and mlbackend_python\processor.

estimate()

core_analytics\regressor::estimate	(		$uniqueid,
		stored_file	$dataset,
			$outputdir )

Estimates linear values for the provided dataset samples.

Parameters

string	$uniqueid
stored_file	$dataset
mixed	$outputdir

Return values

void

Implemented in mlbackend_php\processor, and mlbackend_python\processor.

evaluate_regression()

core_analytics\regressor::evaluate_regression	(		$uniqueid,
			$maxdeviation,
			$niterations,
		stored_file	$dataset,
			$outputdir,
			$trainedmodeldir )

Evaluates this processor regression model using the provided supervised learning dataset.

Parameters

string	$uniqueid
float	$maxdeviation
int	$niterations
stored_file	$dataset
string	$outputdir
string	$trainedmodeldir

Return values

stdClass

Implemented in mlbackend_php\processor, and mlbackend_python\processor.

is_ready()

core_analytics\predictor::is_ready ( )

inherited

Is it ready to predict?

Return values

bool

Implemented in mlbackend_php\processor, and mlbackend_python\processor.

train_regression()

core_analytics\regressor::train_regression	(		$uniqueid,
		stored_file	$dataset,
			$outputdir )

Train this processor regression model using the provided supervised learning dataset.

Parameters

string	$uniqueid
stored_file	$dataset
string	$outputdir

Return values

stdClass

Implemented in mlbackend_php\processor, and mlbackend_python\processor.

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The documentation for this interface was generated from the following file:

• analytics/classes/regressor.php