{"push_id":2996934280,"size":1,"distinct_size":1,"ref":"refs/heads/master","head":"2d083d03cf3ad794b49abf7d76f4e82a8e740f91","before":"aca938c18b5d7878c624f0a3d7c2adf92cc33718","commits":[{"sha":"2d083d03cf3ad794b49abf7d76f4e82a8e740f91","author":{"name":"rramachandran05","email":"41f049bf9bb02648b846b8a4611981daa65a34d9@gmail.com"},"message":"Notebook capturing some LSTM Tuning Experiments\n\nExperiment1: Using data without TA indicators as features\r\nResult: 66%  Accuracy\r\n\r\nExperiment 2: Using TA indicators as features\r\nResult: 83% Accuracy\r\n\r\nDiscover an Error - shifting the time series the wrong way - hence the predictions were laggy. It should be shifted +1.. not -1 \r\nNow the results are not laggy\r\n\r\nSuspect that accuracy is low because of the scaling based normatilization done for the entire time series of data. The price increase over time may be causing issues.\r\n\r\nNeed to develop a new normalization function that changes over time - based on rate of change in stock price","distinct":true,"url":"https://api.github.com/repos/rramachandran05/LSTM/commits/2d083d03cf3ad794b49abf7d76f4e82a8e740f91"}]}
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