From a2002894eb5679006f0f7b89b2294ab83c8213c1 Mon Sep 17 00:00:00 2001 From: Nevena Bojovic Date: Mon, 11 Apr 2022 23:10:56 +0200 Subject: Za regresioni i binarni-klasifikacioni problem, ucitavanje broja neurona po slojevima, nije vise fiksan broj neurona po sloju. --- backend/microservice/api/ml_service.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) (limited to 'backend/microservice/api') diff --git a/backend/microservice/api/ml_service.py b/backend/microservice/api/ml_service.py index 0aed3dc9..b5f5e9bf 100644 --- a/backend/microservice/api/ml_service.py +++ b/backend/microservice/api/ml_service.py @@ -198,7 +198,7 @@ def train(dataset, params, callback): random=123 else: random=0 - x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.5,random_state=0) + x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.5,random_state=random) # # Skaliranje vrednosti # @@ -246,7 +246,9 @@ def train(dataset, params, callback): classifier=tf.keras.Sequential() for func in params["hiddenLayerActivationFunctions"]: - classifier.add(tf.keras.layers.Dense(units=hidden_layer_neurons,activation=func)) + layers = params["hiddenLayers"] + for numNeurons in params["hiddenLayerNeurons"]: + classifier.add(tf.keras.layers.Dense(units=numNeurons,activation=func)) output_func = params["outputLayerActivationFunction"] if(problem_type!="regresioni"): -- cgit v1.2.3