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your code in main.py line189, the code of getting data is below, why do you use companies' stock price to predict NASDAQ-100 Index?
raw_data = pd.read_csv(os.path.join("data", "nasdaq100_padding.csv"), nrows=100 if debug else None)
logger.info(f"Shape of data: {raw_data.shape}.\nMissing in data: {raw_data.isnull().sum().sum()}.")
targ_cols = ("NDX",)
data, scaler = preprocess_data(raw_data, targ_cols)
NDX should be calculated by these stock prices, isn’t it? why u have to learn the calculation formula by RNN?
The DA-RNN paper gives a time series predicting model, right? But where is your time series predicting? I am confusion.
That's what I found when I read the code repeatedly, If I got wrong or missed something, please tell me.
Thank you.
The text was updated successfully, but these errors were encountered:
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your code in main.py line189, the code of getting data is below, why do you use companies' stock price to predict NASDAQ-100 Index?
NDX should be calculated by these stock prices, isn’t it? why u have to learn the calculation formula by RNN?
The DA-RNN paper gives a time series predicting model, right? But where is your time series predicting? I am confusion.
That's what I found when I read the code repeatedly, If I got wrong or missed something, please tell me.
Thank you.
The text was updated successfully, but these errors were encountered: