Classifier interface.
More...
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| classify ($uniqueid, stored_file $dataset, $outputdir) |
| Classifies the provided dataset samples. More...
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| clear_model ($uniqueid, $modelversionoutputdir) |
| Delete all stored information of the current model id. More...
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| delete_output_dir ($modeloutputdir, $uniqueid) |
| Delete the output directory. More...
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| evaluate_classification ($uniqueid, $maxdeviation, $niterations, stored_file $dataset, $outputdir, $trainedmodeldir) |
| Evaluates this processor classification model using the provided supervised learning dataset. More...
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| is_ready () |
| Is it ready to predict? More...
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| train_classification ($uniqueid, stored_file $dataset, $outputdir) |
| Train this processor classification model using the provided supervised learning dataset. More...
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Classifier interface.
- Copyright
- 2016 David Monllao
- License
- http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
◆ classify()
core_analytics\classifier::classify |
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$uniqueid, |
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stored_file |
$dataset, |
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$outputdir |
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◆ clear_model()
core_analytics\predictor::clear_model |
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$uniqueid, |
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$modelversionoutputdir |
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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
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string | $uniqueid | The site model unique id string |
string | $modelversionoutputdir | The output dir of this model version |
- Return values
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Implemented in mlbackend_php\processor, and mlbackend_python\processor.
◆ delete_output_dir()
core_analytics\predictor::delete_output_dir |
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$modeloutputdir, |
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$uniqueid |
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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
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string | $modeloutputdir | The model directory id (parent of all model versions subdirectories). |
string | $uniqueid | |
- Return values
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Implemented in mlbackend_php\processor, and mlbackend_python\processor.
◆ evaluate_classification()
core_analytics\classifier::evaluate_classification |
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$uniqueid, |
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$maxdeviation, |
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$niterations, |
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stored_file |
$dataset, |
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$outputdir, |
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$trainedmodeldir |
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Evaluates this processor classification model using the provided supervised learning dataset.
- Parameters
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string | $uniqueid | |
float | $maxdeviation | |
int | $niterations | |
stored_file | $dataset | |
string | $outputdir | |
string | $trainedmodeldir | |
- Return values
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Implemented in mlbackend_php\processor, and mlbackend_python\processor.
◆ is_ready()
core_analytics\predictor::is_ready |
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inherited |
◆ train_classification()
core_analytics\classifier::train_classification |
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$uniqueid, |
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stored_file |
$dataset, |
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$outputdir |
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The documentation for this interface was generated from the following file: