Changed ontology generation (addedd NN)

dtim-upc · Jul 15, 2024 · 893fa12 · 893fa12
1 parent fed1b23
commit 893fa12
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Showing 4 changed files with 123 additions and 16 deletions.
diff --git a/Modules/IntentSpecification2WorkflowGenerator/api/functions.py b/Modules/IntentSpecification2WorkflowGenerator/api/functions.py
@@ -167,14 +167,8 @@ def get_custom_ontology(path):
     graph = get_graph_xp()
     ontologies = [
         r'ontologies/tbox.ttl',
-        # r'ontologies/cbox.ttl',
-        # r'ontologies/abox.ttl',
-
-        # r'ontologies/cbox_new.ttl',
-        # r'ontologies/abox_new.ttl',
-
-        r'ontologies/cbox_new_2.ttl',
-        r'ontologies/abox_new_2.ttl',
+        r'ontologies/cbox.ttl',
+        r'ontologies/abox.ttl',
         path
     ]
     for o in ontologies:
@@ -187,14 +181,8 @@ def get_custom_ontology_only_problems():
     graph = get_graph_xp()
     ontologies = [
         r'ontologies/tbox.ttl',
-        # r'ontologies/cbox.ttl',
-        # r'ontologies/abox.ttl',
-
-        # r'ontologies/cbox_new.ttl',
-        # r'ontologies/abox_new.ttl',
-
-        r'ontologies/cbox_new_2.ttl',
-        r'ontologies/abox_new_2.ttl',
+        r'ontologies/cbox.ttl',
+        r'ontologies/abox.ttl',
     ]
     for o in ontologies:
         graph.parse(o, format="turtle")

diff --git a/Modules/IntentSpecification2WorkflowGenerator/ontology_populator/cbox_generator.py b/Modules/IntentSpecification2WorkflowGenerator/ontology_populator/cbox_generator.py
@@ -57,6 +57,7 @@ def add_algorithms(cbox):
         (cb.NaiveBayes, cb.Classification),
         (cb.SVM, cb.Classification),
         (cb.KNN, cb.Classification),
+        (cb.NN, cb.Classification),
 
         # Anomaly Detection
         (cb.OneClassSVM, cb.AnomalyDetection),
@@ -110,6 +111,7 @@ def add_models(cbox):
         'DecisionTreeModel',
         'NormalizerModel',
         'MissingValueModel',
+        'NNModel',
     ]
 
     cbox.add((cb.Model, RDFS.subClassOf, tb.Data))

diff --git a/...ntentSpecification2WorkflowGenerator/ontology_populator/implementations/knime/__init__.py b/...ntentSpecification2WorkflowGenerator/ontology_populator/implementations/knime/__init__.py
@@ -3,6 +3,7 @@
 from .normalization import *
 from .decision_tree import *
 from .svm import *
+from .nn import *
 from .missing_values import *
 from .csv_io import *
 
@@ -18,6 +19,8 @@
     missing_value_applier_implementation,
     csv_reader_implementation,
     csv_writer_implementation,
+    nn_learner_implementation,
+    nn_predictor_implementation,
 ]
 
 components = [
@@ -40,4 +43,9 @@
     missing_value_applier_component,
     csv_reader_local_component,
     csv_writer_local_component,
+    feedforward_learner_component,
+    recurrent_learner_component,
+    convolutional_learner_component,
+    lstm_learner_component,
+    nn_predictor_component,
 ]
diff --git a/Modules/IntentSpecification2WorkflowGenerator/ontology_populator/implementations/knime/nn.py b/Modules/IntentSpecification2WorkflowGenerator/ontology_populator/implementations/knime/nn.py
@@ -0,0 +1,109 @@
+from common import *
+from .knime_implementation import KnimeImplementation, KnimeBaseBundle, KnimeParameter
+from ..core import *
+
+nn_learner_implementation = KnimeImplementation(
+    name='NN Learner',
+    algorithm=cb.NN,
+    parameters=[
+        KnimeParameter("Class column", XSD.string, "$$LABEL$$", 'classcol'),
+        KnimeParameter("NN type", XSD.string, None, 'nn_type'),
+    ],
+    input=[
+        [cb.LabeledTabularDatasetShape, cb.NormalizedTabularDatasetShape, cb.NonNullTabularDatasetShape],
+    ],
+    output=[
+        cb.NNModel,
+    ],
+    implementation_type=tb.LearnerImplementation,
+    knime_node_factory='org.knime.base.node.mine.svm.predictor2.SVMPredictorNodeFactory',
+    knime_bundle=KnimeBaseBundle,
+)
+
+feedforward_learner_component = Component(
+    name='FeedForward NN Learner',
+    implementation=nn_learner_implementation,
+    overriden_parameters=[
+        ('NN type', 'FeedForward'),
+    ],
+    exposed_parameters=[
+        'Class column'
+    ],
+    transformations=[
+    ],
+)
+
+recurrent_learner_component = Component(
+    name='Recurrent NN Learner',
+    implementation=nn_learner_implementation,
+    overriden_parameters=[
+        ('NN type', 'Recurrent'),
+    ],
+    exposed_parameters=[
+        'Class column'
+    ],
+    transformations=[
+    ],
+)
+
+convolutional_learner_component = Component(
+    name='Convolutional NN Learner',
+    implementation=nn_learner_implementation,
+    overriden_parameters=[
+        ('NN type', 'Convolutional'),
+    ],
+    exposed_parameters=[
+        'Class column'
+    ],
+    transformations=[
+    ],
+)
+
+lstm_learner_component = Component(
+    name='LSTM NN Learner',
+    implementation=nn_learner_implementation,
+    overriden_parameters=[
+        ('NN type', 'LSTM'),
+    ],
+    exposed_parameters=[
+        'Class column'
+    ],
+    transformations=[
+    ],
+)
+
+nn_predictor_implementation = KnimeImplementation(
+    name='NN Predictor',
+    algorithm=cb.NN,
+    parameters=[
+        KnimeParameter("Prediction column name", XSD.string, "Prediction ($$LABEL$$)", 'prediction column name'),
+        KnimeParameter("Change prediction", XSD.boolean, False, 'change prediction'),
+        KnimeParameter("Add probabilities", XSD.boolean, False, 'add probabilities'),
+        KnimeParameter("Class probability suffix", XSD.string, "", 'class probability suffix'),
+    ],
+    input=[
+        cb.NNModel,
+        [cb.NormalizedTabularDatasetShape, cb.NonNullTabularDatasetShape]
+    ],
+    output=[
+        cb.LabeledTabularDatasetShape,
+    ],
+    implementation_type=tb.ApplierImplementation,
+    counterpart=nn_learner_implementation,
+    knime_node_factory='org.knime.base.node.mine.svm.predictor2.SVMPredictorNodeFactory',
+    knime_bundle=KnimeBaseBundle,
+)
+
+nn_predictor_component = Component(
+    name='NN Predictor',
+    implementation=nn_predictor_implementation,
+    transformations=[
+
+    ],
+    counterpart=[
+        feedforward_learner_component,
+        recurrent_learner_component,
+        convolutional_learner_component,
+        lstm_learner_component
+    ],
+)