Ive scaled my data to be in the range 0-1. ive used this scaled data to train a deep neural network,
model.fit(xscaled,yscaled, verbose=0,epochs=180, batch_size=70, validation_split=0.2)
ive then used the sklearn rmse function to calculate rmse.
print('rmse',sqrt(metrics.mean_squared_error(y_test,predictions)))
which has given me a value of 0.097. The data set im using has 22 input values, with 3 outputs. Im struggling to understand the single rmse value, considering i have 3 outputs. is the rmse scaled because i scaled the data? ie because the data is scaled from 0-1, and i have an rsme of 0.097, this results in an error of 9.7%? i understand that rsme measures depends on the range of data to how 'good' the model is, but considering i have a multi output model with different ranges for the 3 outputs im not sure how this works. thank you.