Submissions:AlgorithmImplementationExecution

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{{Graphical representation header}}
{{Graphical representation header}}
{{Graphical representation
{{Graphical representation
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|ImageName=AlgorithmImplementationExecution.png
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|ImageName=AlgorithmImplementationExecution_ver2.png
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{{Content OP Proposal Template
{{Content OP Proposal Template
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What is the input to this implementation execution?,
What is the input to this implementation execution?,
What is the output produced by the this implementation execution?,
What is the output produced by the this implementation execution?,
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What task this execution realizes?,
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What algorithm does this execution realize?,
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What task does this execution achieves?,
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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Implementation SubClassOf implements some Algorithm <br>
Implementation SubClassOf implements some Algorithm <br>
Implementation SubClassOf hasParameter some Parameter <br>
Implementation SubClassOf hasParameter some Parameter <br>
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Execution SubClassOfProcess <br>
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Execution SubClassOf Process <br>
-
Execution SubClassOf hasInput some Input <br>
+
Execution SubClassOf hasInput some ParameterSetting <br>
Execution SubClassOf hasInput some ParameterSetting <br>
-
Execution SubClassOf hasOutput some Output <br>
+
Execution SubClassOf realizes some Algorithm <br>
-
Execution SubClassOf realizes some Task <br>
+
Execution SubClassOf achieves some Task <br>
Execution SubClassOf hasDuration some TimeInterval <br>
Execution SubClassOf hasDuration some TimeInterval <br>
Parameter SubClassOf InformationEntity <br>
Parameter SubClassOf InformationEntity <br>
ParameterSetting SubClassOf InformationEntity <br>
ParameterSetting SubClassOf InformationEntity <br>
ParameterSetting SubClassOf specifiedBy some Parameter <br>
ParameterSetting SubClassOf specifiedBy some Parameter <br>
-
ParameterSetting SubClassOf hasValue some refs:Literal <br>
+
ParameterSetting SubClassOf hasValue some rdfs:Literal <br>
Input SubClassOf InformationEntity <br>
Input SubClassOf InformationEntity <br>
Output SubClassOf InformationEntity <br>
Output SubClassOf InformationEntity <br>
Task SubClassOf InformationEntity <br>
Task SubClassOf InformationEntity <br>
Task SubClassOf definedOn some Input
Task SubClassOf definedOn some Input
 +
Top SubClassOf hasInput only Input <br>
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Top SubClassOf hasOutput only Output <br>
 +
|ReusableOWLBuildingBlock=https://github.com/ML-Schema/core/blob/master/AlgorithmImplementationExecution.owl
|ReusableOWLBuildingBlock=https://github.com/ML-Schema/core/blob/master/AlgorithmImplementationExecution.owl
|Scenario=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/). <br> There is an ML Task <code>:task29</code> which is a supervised classification task defined on the dataset <code>:credit-a</code>. This task is realized by the Execution <code>:run100241</code> which executes the Implementation <code>:wekaLogistic</code> of the Algorithm <code>:logisticRegression</code>. <br>The Implementation <code>:wekaLogistic</code> has five hyperparameters (Parameter): <code>:wekaLogisticC</code>, <code>:wekaLogisticDoNotCheckCapabilities</code>, <code>:wekaLogisticM</code>, <code>:wekaLogisticOutputDebugInfo</code>, <code>:wekaLogisticR</code>. The values of two of these hyperparameters are set. The hyper parameter <code>:wekaLogisticM</code> has value set to -1 (expressed via the ParameterSetting <code>:wekaLogisticMSetting29</code>), and the hyper parameter <code>:wekaLogisticR</code> that has its value set to <code>"1.0E-8"^^xsd:float</code> (expressed via the ParameterSetting <code>:wekaLogisticRSetting29</code>). <br> The Execution <code>:run100241</code> has on Input the <code>:credit-a</code> dataset and the parameter settings and its Output is the ML model <code>:wekaLogisticModel100241</code>.
|Scenario=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/). <br> There is an ML Task <code>:task29</code> which is a supervised classification task defined on the dataset <code>:credit-a</code>. This task is realized by the Execution <code>:run100241</code> which executes the Implementation <code>:wekaLogistic</code> of the Algorithm <code>:logisticRegression</code>. <br>The Implementation <code>:wekaLogistic</code> has five hyperparameters (Parameter): <code>:wekaLogisticC</code>, <code>:wekaLogisticDoNotCheckCapabilities</code>, <code>:wekaLogisticM</code>, <code>:wekaLogisticOutputDebugInfo</code>, <code>:wekaLogisticR</code>. The values of two of these hyperparameters are set. The hyper parameter <code>:wekaLogisticM</code> has value set to -1 (expressed via the ParameterSetting <code>:wekaLogisticMSetting29</code>), and the hyper parameter <code>:wekaLogisticR</code> that has its value set to <code>"1.0E-8"^^xsd:float</code> (expressed via the ParameterSetting <code>:wekaLogisticRSetting29</code>). <br> The Execution <code>:run100241</code> has on Input the <code>:credit-a</code> dataset and the parameter settings and its Output is the ML model <code>:wekaLogisticModel100241</code>.

Revision as of 17:07, 27 August 2016


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Current revision ID: 12850

Graphical representation

Diagram

Image:AlgorithmImplementationExecution_ver2.png

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:

General, Software, Software Engineering, Workflow

Competency Questions:
  • Which algorithm is implemented by this implementation?
  • 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 algorithm does this execution realize?
  • What task does this execution achieves?
  • 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 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 (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 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:


Elements

The AlgorithmImplementationExecution Content OP locally defines the following ontology elements:

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