Diagram
| Name: | AlgorithmImplementationExecution |
| Submitted by: | AgnieszkaLawrynowicz, DiegoEsteves, PancePanov, SasoDzeroski, TommasoSoru, JoaquinVanschoren |
| Also Known As: | |
| Intent: | To model algorithm specifications, their implementations and executions, together with parameters of implementations, settings of the parameters for the execution, and inputs the execution consumes (e.g., data) and outputs the execution produces (e.g., models, reports). |
| Domains: | General, Software, Software Engineering, Workflow |
| Competency Questions: | |
| Solution description: | Beloit it is provided the formalization of the pattern in the Web Ontology Language (OWL) in Manchester syntax:Algorithm SubClassOf InformationEntity Implementation SubClassOf InformationEntity Implementation SubClassOf implements some Algorithm Implementation SubClassOf hasParameter some Parameter Execution SubClassOf Process Execution SubClassOf hasInput some ParameterSetting Execution SubClassOf realizes some Algorithm Execution SubClassOf achieves some Task Execution SubClassOf hasDuration some TimeInterval Parameter SubClassOf InformationEntity ParameterSetting SubClassOf InformationEntity ParameterSetting SubClassOf specifiedBy some Parameter ParameterSetting SubClassOf hasValue some rdfs:Literal Input SubClassOf InformationEntity Output SubClassOf InformationEntity Task SubClassOf InformationEntity Task SubClassOf definedOn some Input Top SubClassOf hasInput only Input Top SubClassOf hasOutput only Output |
| Reusable OWL Building Block: | [https://github.com/ML-Schema/core/blob/master/AlgorithmImplementationExecution.owl](http://ontologydesignpatterns.org/wiki/index.php?title=Special:ClickHandler&link=https://github.com/ML-Schema/core/blob/master/AlgorithmImplementationExecution.owl&message=OWL building block&from_page_id=4056&update=) (0) |
| Consequences: | |
| Scenarios: | Consider a scenario in machine learning (ML) domain. The scenario deals with a machine learning task completion and it is based on an example derived from the OpenML portal (http://www.openml.org/). There is an ML Task :task29 which is a supervised classification task defined on the dataset :credit-a. This task is achieved by the Execution :run100241 which executes the Implementation :wekaLogistic of the Algorithm :logisticRegression. The Implementation :wekaLogistic has five hyperparameters (Parameter): :wekaLogisticC, :wekaLogisticDoNotCheckCapabilities, :wekaLogisticM, :wekaLogisticOutputDebugInfo, :wekaLogisticR. The values of two of these hyperparameters are set. The hyper parameter :wekaLogisticM has value set to -1 (expressed via the ParameterSetting :wekaLogisticMSetting29), and the hyper parameter :wekaLogisticR that has its value set to "1.0E-8"^^xsd:float (expressed via the ParameterSetting :wekaLogisticRSetting29). The Execution :run100241 has on Input the :credit-a dataset and the parameter settings and its Output is the ML model :wekaLogisticModel100241. |
| Known Uses: | ML Schema, DMOP, Function Ontology, MEX, OBI, OntoDM |
| Web References: | |
| Other References: | |
| Examples (OWL files): | |
| Extracted From: | |
| Reengineered From: | |
| Has Components: | |
| Specialization Of: | |
| Related CPs: |
The AlgorithmImplementationExecution Content OP locally defines the following ontology elements:
Scenarios about AlgorithmImplementationExecution No scenario is added to this Content OP.
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