I have extented the DMOP ontology for meta-learning using protege. I am able to run the reasoner on TBox.
I am populating this ontology using owlready. However, when I run the reasoner I get the following error:
Hermit:
Pellet:
There is nothing on the specified line.
I do not have any rules defined in the ontology at this point.
Any idea how can I solve? Because I have multiple datapoints, I am unable to paste the entire code here. But here is the snippet.
Assume I have loaded all the namespaces. I am able to save this generated RDF file, but not the reasoning.
When I run Hermit or Pellet using protege on the knowledge base the protege classifies classes and object properties. While running the reasoner on data properties, it gets stuck.
for i in range(len(df)):
featureSelectionTask = dmop.FeatureSelectionTask()
mtla = mtl.MetaLearningAlgorithm()
fileName = df['File'][i]
fileObject = dmop.DataSetClass(fileName)
mtla.hasMetaObjective.append(featureSelectionTask)
featureSelectionTask.specifiesInputClass.append(fileObject)
outClass =dmop.StructuredPredictionModelClass()
featureSelectionTask.specifiesOutputClass.append(outClass)
outClass.hasValue.append(df['FeatureAlgo'][i])
nFeatures = dmop1.NumberOfFeatures()
fileObject.hasQuality.append(nFeatures)
nFeatures.hasValue.append(int(df['nr_attr'][i]))
nFeatures.hasBinValue.append(str(df['nr_attr_bins'][i]))
......
I solved the pellet issue by setting JAVA_HOME variable for owlready. Still I have the same problem for Hermit.