Submissions:AlgorithmImplementationExecution
From Odp
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{{Content OP Proposal Template | {{Content OP Proposal Template | ||
| - | |SubmittedBy=AgnieszkaLawrynowicz DiegoEsteves PancePanov SasoDzeroski TommasoSoru JoaquinVanschoren | + | |SubmittedBy=AgnieszkaLawrynowicz, DiegoEsteves, PancePanov, SasoDzeroski, TommasoSoru, JoaquinVanschoren |
|Name=AlgorithmImplementationExecution | |Name=AlgorithmImplementationExecution | ||
|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). | |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). | ||
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What is the duration of this execution? | What is the duration of this execution? | ||
What is the input this task is defined on? | What is the input this task is defined on? | ||
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|ContentODPDescription=Beloit it is provided the formalization of the pattern in the Web Ontology Language (OWL) in Manchester syntax: | |ContentODPDescription=Beloit it is provided the formalization of the pattern in the Web Ontology Language (OWL) in Manchester syntax: | ||
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|KnownUse=ML Schema, DMOP, OntoDM, OBI, MEX, Function Ontology | |KnownUse=ML Schema, DMOP, OntoDM, OBI, MEX, Function Ontology | ||
|ReengineeredFrom=ML Schema, https://www.w3.org/community/ml-schema/ | |ReengineeredFrom=ML Schema, https://www.w3.org/community/ml-schema/ | ||
| - | |HasComponent= | + | |HasComponent=TimeInterval |
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{{Element list header}} | {{Element list header}} | ||
Revision as of 09:02, 6 July 2016
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Graphical representation
Diagram
General description
| 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: | |
| Competency Questions: |
What are the implementations of this algorithm? Which implementation is executed? What are the parameters of this implementation? What are the parameter settings of particular parameters in this execution? What is the input to this implementation execution? What is the output produced by the this implementation execution? What task this execution realizes? What is the duration of this execution? What is the input this task is defined on? |
| 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 SubClassOfProcess Execution SubClassOf hasInput some Input Execution SubClassOf hasInput some ParameterSetting Execution SubClassOf hasOutput some Output Execution SubClassOf realizes 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 |
| Reusable OWL Building Block: | https://github.com/ML-Schema/core/blob/master/AlgorithmImplementationExecution.owl (0) |
| Consequences: | |
| Scenarios: | Consider a scenario in machine learning (ML) domain. The scenario deals with a machine learning task realization 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 realized 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 hyperparameter :wekaLogisticM has value set to -1 (expressed via the ParameterSetting :wekaLogisticMSetting29), and the hyperparameter :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, OntoDM, OBI, MEX, Function Ontology |
| Web References: | |
| Other References: | |
| Examples (OWL files): | |
| Extracted From: | |
| Reengineered From: |
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| Has Components: | |
| Specialization Of: | |
| Related CPs: |
Elements
The AlgorithmImplementationExecution Content OP locally defines the following ontology elements:
Additional information
Scenarios
No scenario is added to this Content OP.
Reviews
There is no review about this proposal. This revision (revision ID 12553) takes in account the reviews: none
Other info at evaluation tab
Modeling issues
There is no Modeling issue related to this proposal.
References
