diff options
Diffstat (limited to 'backend/microservice/api/newmlservice.py')
| -rw-r--r-- | backend/microservice/api/newmlservice.py | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index 85d8fb71..2f08d4b4 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -183,7 +183,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): columnTypes=paramsExperiment['columnTypes'] for i in range(len(columnInfo)): col=columnInfo[i] - if(columnTypes[i]=="categorical"): + if(columnTypes[i]=="categorical" and col['columnName'] in paramsExperiment['inputColumns']): data[col['columnName']]=data[col['columnName']].apply(str) kategorijskekolone.append(col['columnName']) #kategorijskekolone=data.select_dtypes(include=['object']).columns @@ -365,7 +365,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): - classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt, metrics =paramsModel['metrics']) + classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt, metrics = ['accuracy','mae','mse']) history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) @@ -419,7 +419,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): classifier.add(tf.keras.layers.Dense(units=1, activation=paramsModel['outputLayerActivationFunction']))#izlazni sloj - classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics =paramsModel['metrics']) + classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics = ['accuracy','mae','mse']) history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) hist=history.history @@ -468,7 +468,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): classifier.add(tf.keras.layers.Dense(units=1,activation=paramsModel['outputLayerActivationFunction'])) - classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics =paramsModel['metrics']) + classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics = ['accuracy','mae','mse']) history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) hist=history.history @@ -638,7 +638,7 @@ def manageH5(dataset,params,h5model): h5model.summary() #ann_viz(h5model, title="My neural network") - h5model.compile(loss=params['lossFunction'], optimizer=params['optimizer'], metrics=params['metrics']) + h5model.compile(loss=params['lossFunction'], optimizer=params['optimizer'], metrics = ['accuracy','mae','mse']) history=h5model.fit(x2, y2, epochs = params['epochs'],batch_size=int(params['batchSize'])) |