Comparing Long Term Short Memory (LSTM) & Gated Re-current Unit (GRU) during forecasting of oil price .Exploring multivariate relationships between West Texas Intermediate and S&P 500, Dow Jones Utility Avg, US Dollar Index Futures , US 10 Yr Treasury Bonds , Gold Futures.
hi
i got error when running this code
##Forecasting Using Z-Score Outlier Removal
sc3 = MinMaxScaler(feature_range=(0,1))
sc4 = MinMaxScaler(feature_range=(0,1))
gru_model(sc3,z_train,3)
TypeError: Inputs to a layer should be tensors. Got: MinMaxScaler()
Good morning, Thanks for your contribution and share. Really a good job. Also I have read your paper about the prediction.
There is a place , I could not understand , Coud you give me some guidance about how to how to transform Mahalanobis transformation is performed on WTI, and three features GOLD, USDINDEX, and US10B ?
Mahalanobis is 1D array, I am not sure how to transform for the target WTI .
Thank you very much. When you are Feel free , I am looking forward to your reply ,
Good morning, I saw your multivariate analysis for WTI and would like to speak with you privately to discuss some possibile partnerships. Also I would like to note that removing the data from the financial crisis might not have been the best idea in my honest opinion. Feel free if interested to message me @ [email protected]