Raku DSL::Entity::MachineLearning

Raku grammar classes for Machine Learning (ML) entities (names.)

Installation

zef install https://github.com/antononcube/Raku-DSL-Entity-MachineLearning.git

Usage examples

use DSL::Entity::MachineLearning;
use DSL::Entity::MachineLearning::ResourceAccess;

my $pCOMMAND = DSL::Entity::MachineLearning::Grammar;
$pCOMMAND.set-resources(DSL::Entity::MachineLearning::resource-access-object());

say $pCOMMAND.parse('DecisionTree', rule => 'machine-learning-entity-command');
say $pCOMMAND.parse('gradient boosted trees', rule => 'machine-learning-entity-command');
say $pCOMMAND.parse('roc curve', rule => 'machine-learning-entity-command');

# ｢DecisionTree｣
#  classifier-entity-command => ｢DecisionTree｣
#   entity-classifier-name => ｢DecisionTree｣
#    0 => ｢DecisionTree｣
#     word-value => ｢DecisionTree｣
# ｢gradient boosted trees｣
#  classifier-entity-command => ｢gradient boosted trees｣
#   entity-classifier-name => ｢gradient boosted trees｣
#    0 => ｢gradient boosted trees｣
#     word-value => ｢gradient｣
#     word-value => ｢boosted｣
#     word-value => ｢trees｣
# ｢roc curve｣
#  classifier-measurement-entity-command => ｢roc curve｣
#   entity-classifier-measurement-name => ｢roc curve｣
#    0 => ｢roc curve｣
#     word-value => ｢roc｣
#     word-value => ｢curve｣

Command line interface

The package provide as Command Line Interface (CLI) to its functionalities:

> ToMachineLearningEntityCode --help
# Usage:
#   ToMachineLearningEntityCode <command> [--target=<Str>] [--user=<Str>] -- Conversion of (natural) DSL machine learning entity name into code.
#   ToMachineLearningEntityCode <target> <command> [--user=<Str>] -- Both target and command as arguments.
#
#     <command>         natural language command (DSL commands)
#     --target=<Str>    target language/system/package (defaults to 'WL-System') [default: 'WL-System']
#     --user=<Str>      user identifier (defaults to '') [default: '']
#     <target>          Programming language.

Remark: (Currently) the CLI script always returns results in JSON format.

References

Classify and methods

[WRI1] Wolfram Research, Inc., Classify.

[WRI2] Wolfram Research, Inc., Machine Learning Methods.

Repositories

[AAr1] Anton Antonov, DSL::English::ClassificationWorkflows Raku package, (2020-2022), GitHub/antononcube.

[AAr2] Anton Antonov, DSL::Shared Raku package, (2020), GitHub/antononcube.

[AAr3] Anton Antonov, DSL::Entity::Geographics Raku package, (2021), GitHub/antononcube.

[AAr4] Anton Antonov, DSL::Entity::Jobs Raku package, (2021), GitHub/antononcube.

[AAr5] Anton Antonov, DSL::Entity::Foods Raku package, (2021), GitHub/antononcube.

[AAr6] Anton Antonov, DSL::Entity::Metadata Raku package, (2021), GitHub/antononcube.