I'm trying to predict the Pollution using a Multivariate and Multi-step LSTM code, I've been following this tutorial.
I've been following the code until the end, but couldn't understand where the code writer determined the Pollution column to be the code output (predicting the Pollution column instead of an other column?) I'm new to python, and it got me confused.
At first, I thought that this is the part of the code where we define it, but I was wrong:
# invert scaling for forecast pred_scaler = MinMaxScaler(feature_range=(0, 1)).fit(dataset.values[:,0].reshape(-1, 1)) inv_yhat = pred_scaler.inverse_transform(yhat) print(inv_yhat.shape) # invert scaling for actual inv_y = pred_scaler.inverse_transform(test_y) print(inv_y.shape)
Any explanations on how he determined the pollution column out of the 7 other columns to be the output?