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I started poking at this out of curiosity, and a desire to begin sharpening my TensorFlow axe, and one thing remains unclear. They give you two spreadsheets, one being the training data and the other is the tournament data (what you need to predict on). Each entry in the spreadsheet is 21 features and a single binary class. The latter is what you predict. But for the submissions they request a probability, not a class. They don't explain what "probability" here means. Does it mean probability of class 0? Probability of class 1? Probability of the moon exploding on a Thursday?

Overall interesting idea. Undecided whether it's real/scam/fake, but definitely very interesting at face value. I just wish their documentation was more clear. Seems kind of important...

EDIT: Found a comment on Reddit that indicates that it means probability of class 1 (https://www.reddit.com/r/MachineLearning/comments/3wdr9e/num...)



Have you found any good TensorFlow examples which handle financial or time series data like this? Please do share! Most of the examples I find are either image processing or text processing. Rarely time series or traditional DB type data.


Generally people use a LTSM for time series if they want to use a NN approach.

See http://robromijnders.github.io/LSTM_tsc/




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