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Developer Documentation
- Bug fixes for general core bugs in 3.10.x will end 8 November 2021 (12 months).
- Bug fixes for security issues in 3.10.x will end 9 May 2022 (18 months).
- PHP version: minimum PHP 7.2.0 Note: minimum PHP version has increased since Moodle 3.8. PHP 7.3.x and 7.4.x are supported too.
/analytics/tests/ -> prediction_test.php (source)
Differences Between: [Versions 310 and 311] [Versions 310 and 400] [Versions 310 and 401] [Versions 310 and 402] [Versions 310 and 403] [Versions 39 and 310]
Unit tests for evaluation, training and prediction. NOTE: in order to execute this test using a separate server for the python ML backend you need to define these variables in your config.php file:
| Copyright: | 2017 David Monllaó {@link http://www.davidmonllao.com} |
| License: | http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later |
| File Size: | 996 lines (43 kb) |
| Included or required: | 0 times |
| Referenced: | 0 times |
| Includes or requires: | 10 files analytics/tests/fixtures/test_indicator_null.php analytics/tests/fixtures/test_indicator_fullname.php analytics/tests/fixtures/test_indicator_min.php course/lib.php analytics/tests/fixtures/test_indicator_random.php analytics/tests/fixtures/test_target_shortname_multiclass.php analytics/tests/fixtures/test_indicator_max.php analytics/tests/fixtures/test_static_target_shortname.php analytics/tests/fixtures/test_indicator_multiclass.php analytics/tests/fixtures/test_target_shortname.php |
Defines 1 class
core_analytics_prediction_testcase:: (24 methods):
tearDown()
test_static_prediction()
test_model_contexts()
test_ml_training_and_prediction()
provider_ml_training_and_prediction()
test_ml_export_import()
provider_ml_processors()
test_ml_classifiers_return()
provider_ml_classifiers_return()
test_ml_multi_classifier()
provider_test_multi_classifier()
test_ml_evaluation_configuration()
test_ml_evaluation_trained_model()
test_read_indicator_calculations()
test_not_null_samples()
provider_ml_test_evaluation_configuration()
add_random_model()
add_perfect_model()
add_multiclass_model()
generate_courses()
generate_courses_multiclass()
set_forced_config()
is_predictions_processor_ready()
add_prediction_processors()
Class: core_analytics_prediction_testcase - X-Ref
Unit tests for evaluation, training and prediction.| tearDown() X-Ref |
| Purge all the mlbackend outputs. This is done automatically for mlbackends using the web server dataroot but other mlbackends may store files elsewhere and these files need to be removed. return: null |
| test_static_prediction() X-Ref |
| test_static_prediction return: void |
| test_model_contexts() X-Ref |
| test_model_contexts |
| test_ml_training_and_prediction($timesplittingid, $predictedrangeindex, $nranges, $predictionsprocessorclass,$forcedconfig) X-Ref |
| test_ml_training_and_prediction param: string $timesplittingid param: int $predictedrangeindex param: int $nranges param: string $predictionsprocessorclass param: array $forcedconfig return: void |
| provider_ml_training_and_prediction() X-Ref |
| provider_ml_training_and_prediction return: array |
| test_ml_export_import($predictionsprocessorclass, $forcedconfig) X-Ref |
| test_ml_export_import param: string $predictionsprocessorclass The class name param: array $forcedconfig |
| provider_ml_processors() X-Ref |
| provider_ml_processors return: array |
| test_ml_classifiers_return($success, $nsamples, $classes, $predictionsprocessorclass, $forcedconfig) X-Ref |
| Test the system classifiers returns. This test checks that all mlbackend plugins in the system are able to return proper status codes even under weird situations. param: int $success param: int $nsamples param: int $classes param: string $predictionsprocessorclass param: array $forcedconfig return: void |
| provider_ml_classifiers_return() X-Ref |
| test_ml_classifiers_return provider We can not be very specific here as test_ml_classifiers_return only checks that mlbackend plugins behave and expected and control properly backend errors even under weird situations. return: array |
| test_ml_multi_classifier($timesplittingid, $predictionsprocessorclass, $forcedconfig) X-Ref |
| Tests correct multi-classification. param: string $timesplittingid param: string $predictionsprocessorclass param: array|null $forcedconfig |
| provider_test_multi_classifier() X-Ref |
| Provider for the multi_classification test. return: array |
| test_ml_evaluation_configuration($modelquality, $ncourses, $expected, $predictionsprocessorclass,$forcedconfig) X-Ref |
| Basic test to check that prediction processors work as expected. param: string $modelquality param: int $ncourses param: array $expected param: string $predictionsprocessorclass param: array $forcedconfig return: void |
| test_ml_evaluation_trained_model($predictionsprocessorclass, $forcedconfig) X-Ref |
| Tests the evaluation of already trained models. param: string $predictionsprocessorclass param: array $forcedconfig return: null |
| test_read_indicator_calculations() X-Ref |
| test_read_indicator_calculations return: void |
| test_not_null_samples() X-Ref |
| test_not_null_samples |
| provider_ml_test_evaluation_configuration() X-Ref |
| provider_ml_test_evaluation_configuration return: array |
| add_random_model() X-Ref |
| add_random_model return: \core_analytics\model |
| add_perfect_model($targetclass = 'test_target_shortname') X-Ref |
| add_perfect_model param: string $targetclass return: \core_analytics\model |
| add_multiclass_model($targetclass = 'test_target_shortname_multiclass') X-Ref |
| Generates model for multi-classification param: string $targetclass return: \core_analytics\model |
| generate_courses($ncourses, array $params = []) X-Ref |
| Generates $ncourses courses param: int $ncourses The number of courses to be generated. param: array $params Course params return: null |
| generate_courses_multiclass($ncourses, array $params = []) X-Ref |
| Generates ncourses for multi-classification param: int $ncourses The number of courses to be generated. param: array $params Course params return: null |
| set_forced_config($forcedconfig) X-Ref |
| Forces some configuration values. param: array $forcedconfig |
| is_predictions_processor_ready(string $predictionsprocessorclass) X-Ref |
| Is the provided processor ready using the current configuration in the site? param: string $predictionsprocessorclass return: \core_analytics\predictor |
| add_prediction_processors($cases) X-Ref |
| add_prediction_processors param: array $cases return: array |
