Moodle PHP Documentation 4.2
Moodle 4.2.8 (Build: 20240610) (2d41ac46f45)
core_analytics\regressor Interface Reference

Regressors interface. More...

Inheritance diagram for core_analytics\regressor:
core_analytics\predictor mlbackend_php\processor mlbackend_python\processor

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.

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$uniqueidThe site model unique id string
string$modelversionoutputdirThe 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$modeloutputdirThe model directory id (parent of all model versions subdirectories).
string$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.


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