def get_model(x, y, model_config):
if model_config["model"]["type"] == "regression":
regression_model = PolynomialRegressionModel(
model_config["model_name"],
model_config["model"]["polynomial_degree"])
regression_model.train(x, y)
return regression_model
elif model_config["model"]["type"] == "neural_net":
neural_net_model = NeuralNetModel(model_config["model_name"])
neural_net_model.train(x, y, model_config["model"])
return neural_net_model
return None
def get_model(x, y, model_config):
if model_config["model"]["type"] == "regression":
regression_model = PolynomialRegressionModel(
model_config["model_name"],
model_config["model"]["polynomial_degree"])
regression_model.train(x, y)
return regression_model
elif model_config["model"]["type"] == "neural_net":
neural_net_model = NeuralNetModel(model_config["model_name"])
neural_net_model.train(x, y,
model_config["model"]["hidden_layer_sizes"],
model_config["model"]["learning_rate"],
model_config["model"]["max_iter"])
return neural_net_model
return None