You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Goal: Predict multivariate time-series with exogenous variables
Assuming a pandas DataFrame with T rows and M+N columns, where each row t represents one time stamp, M columns represent the corresponding RNN output at time t, and N columns represent the corresponding RNN input at time t.
Ideally, the user can hand the dataframe, or two data frames, say, X (TxN) for the input and y (TxM) for the output, to the theanets API and the API takes care of reformatting it into the required 3 dimensional format required to train RNNs.
The text was updated successfully, but these errors were encountered:
Goal: Predict multivariate time-series with exogenous variables
Assuming a pandas DataFrame with T rows and M+N columns, where each row t represents one time stamp, M columns represent the corresponding RNN output at time t, and N columns represent the corresponding RNN input at time t.
Ideally, the user can hand the dataframe, or two data frames, say, X (TxN) for the input and y (TxM) for the output, to the theanets API and the API takes care of reformatting it into the required 3 dimensional format required to train RNNs.
The text was updated successfully, but these errors were encountered: