Mlp, Time Series Forecasting, Data Science, Machine Learning, TensorFlow.
series_to_supervised(data, window=1, lag=1, dropnan=True): cols = [] names = [] # Input sequence (t-n, ... t-1) for i in range(window, 0, -1): cols.append(data.shift(i)) names += [('%s(t-%d)' % (col, i)) for col in data.columns] # Current timestep (t=0) cols.append(data) names += [('%s(t)' % (col))