Submissions:AlgorithmImplementationExecution - Revision history

AgnieszkaLawrynowicz at 17:19, 27 August 2016

2016-08-27T17:19:49Z

AgnieszkaLawrynowicz at 17:19, 27 August 2016

2016-08-27T17:19:01Z

AgnieszkaLawrynowicz at 17:07, 27 August 2016

2016-08-27T17:07:21Z

AgnieszkaLawrynowicz at 23:05, 8 July 2016

2016-07-08T23:05:36Z

AgnieszkaLawrynowicz at 09:17, 6 July 2016

2016-07-06T09:17:23Z

AgnieszkaLawrynowicz at 09:14, 6 July 2016

2016-07-06T09:14:21Z

AgnieszkaLawrynowicz at 09:12, 6 July 2016

2016-07-06T09:12:13Z

AgnieszkaLawrynowicz at 09:04, 6 July 2016

2016-07-06T09:04:41Z

AgnieszkaLawrynowicz at 09:02, 6 July 2016

2016-07-06T09:02:41Z

AgnieszkaLawrynowicz at 09:00, 6 July 2016

2016-07-06T09:00:45Z

@@ Line 38: / Line 38: @@
 Output SubClassOf InformationEntity <br>
 Task SubClassOf InformationEntity <br>
-Task SubClassOf definedOn some Input
+Task SubClassOf definedOn some Input <br>
 Top SubClassOf hasInput only Input <br>
 Top SubClassOf hasOutput only Output <br>

@@ Line 41: / Line 41: @@
 Top SubClassOf hasInput only Input <br>
 Top SubClassOf hasOutput only Output <br>
 |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 completion 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 achieved 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>.
 |KnownUse=ML Schema, DMOP, Function Ontology, MEX, OBI, OntoDM
 |ReengineeredFrom=ML Schema, https://www.w3.org/community/ml-schema/

@@ Line 2: / Line 2: @@
 {{Graphical representation header}}
 {{Graphical representation
-|ImageName=AlgorithmImplementationExecution.png
+|ImageName=AlgorithmImplementationExecution_ver2.png
 }}
 {{Content OP Proposal Template
@@ Line 16: / Line 16: @@
 What is the input to this implementation execution?,
 What is the output produced by the this implementation execution?,
-What task this execution realizes?,
+What algorithm does this execution realize?,
 What is the duration of this execution?,
 What is the input this task is defined on?
@@ Line 25: / Line 26: @@
 Implementation SubClassOf implements some Algorithm <br>
 Implementation SubClassOf hasParameter some Parameter <br>
-Execution SubClassOfProcess <br>
+Execution SubClassOf Process <br>
-Execution SubClassOf hasInput some Input <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>
 Parameter SubClassOf InformationEntity <br>
 ParameterSetting SubClassOf InformationEntity <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>
 Output SubClassOf InformationEntity <br>
 Task SubClassOf InformationEntity <br>
 Task SubClassOf definedOn some Input
 |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>.

@@ Line 44: / Line 44: @@
 |ReengineeredFrom=ML Schema, https://www.w3.org/community/ml-schema/
 |HasComponent=TimeInterval
 }}
 {{Element list header}}

@@ Line 40: / Line 40: @@
 Task SubClassOf definedOn some Input
 |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>). 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>.
-|KnownUse=ML Schema, DMOP, OntoDM, OBI, MEX, Function Ontology
+|KnownUse=ML Schema, DMOP, Function Ontology, MEX, OBI, OntoDM
 |ReengineeredFrom=ML Schema, https://www.w3.org/community/ml-schema/
 |HasComponent=TimeInterval

@@ Line 21: / Line 21: @@
 |ContentODPDescription=Beloit it is provided the formalization of the pattern in the Web Ontology Language (OWL) in Manchester syntax:
-Algorithm SubClassOf InformationEntity,
+Algorithm SubClassOf InformationEntity <br>
-Implementation SubClassOf InformationEntity,
+Implementation SubClassOf InformationEntity <br>
-Implementation SubClassOf implements some Algorithm,
+Implementation SubClassOf implements some Algorithm <br>
-Implementation SubClassOf hasParameter some Parameter,
+Implementation SubClassOf hasParameter some Parameter <br>
-Execution SubClassOfProcess,
+Execution SubClassOfProcess <br>
-Execution SubClassOf hasInput some Input,
+Execution SubClassOf hasInput some Input <br>
-Execution SubClassOf hasInput some ParameterSetting,
+Execution SubClassOf hasInput some ParameterSetting <br>
-Execution SubClassOf hasOutput some Output,
+Execution SubClassOf hasOutput some Output <br>
-Execution SubClassOf realizes some Task,
+Execution SubClassOf realizes some Task <br>
-Execution SubClassOf hasDuration some TimeInterval,
+Execution SubClassOf hasDuration some TimeInterval <br>
-Parameter SubClassOf InformationEntity,
+Parameter SubClassOf InformationEntity <br>
-ParameterSetting SubClassOf InformationEntity,
+ParameterSetting SubClassOf InformationEntity <br>
-ParameterSetting SubClassOf specifiedBy some Parameter,
+ParameterSetting SubClassOf specifiedBy some Parameter <br>
-ParameterSetting SubClassOf hasValue some refs:Literal,
+ParameterSetting SubClassOf hasValue some refs:Literal <br>
-Input SubClassOf InformationEntity,
+Input SubClassOf InformationEntity <br>
-Output SubClassOf InformationEntity,
+Output SubClassOf InformationEntity <br>
-Task SubClassOf InformationEntity,
+Task SubClassOf InformationEntity <br>
 Task SubClassOf definedOn some Input
 |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/). 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>. 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>). 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>). 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>.
 |KnownUse=ML Schema, DMOP, OntoDM, OBI, MEX, Function Ontology
 |ReengineeredFrom=ML Schema, https://www.w3.org/community/ml-schema/

@@ Line 1: / Line 1: @@
 {{Content_OP_Proposal_toolbar}}
 {{Graphical representation header}}
-{{Graphical representation
+{{Graphical representation}}
-|ImageName=
 }}
 {{Content OP Proposal Template
-|SubmittedBy=AgnieszkaLawrynowicz
+|SubmittedBy=AgnieszkaLawrynowicz DiegoEsteves PancePanov SasoDzeroski  TommasoSoru JoaquinVanschoren
-|ReusableOWLBuildingBlock=https://github.com/ML-Schema/core/blob/master/AlgorithmImplementationExecution.owl
 |Name=AlgorithmImplementationExecution
 }}
 {{Element list header}}
 {{Additional information header}}
 {{Scenarios about me}}
-{{Reviews about me}}{{Modeling issues about me}}{{My references}}
+{{Reviews about me}}