Using Rolling Forecast Origin Resampling in R for Neural Network Time Series

I'll try to answer to your questions. What does the initialWindow mean in layman's terms? Put in simple terms, the initialWindow is the size (number of samples or row's dataset) of the training dataset used by the MLP (Multi-Layer Perceptron neural network) for its training stage used for each resample. What does the fixedWindow mean in layman's terms? This means that for each resample, the size of the training dataset does not change but remain the same; it's simple shifted onwards by an amount specified by horizon (in your case set to 1, i.e. a one step-ahead forecast) How is the output of the model interpreted?