Hi everyone !
There is an example of modelling stock market data:
http://scikit-learn.org/0.12/auto_examples/plot_hmm_stock_analysis.html#example-plot-hmm-stock-analysis-py
At the end we have learned transition matrix between hidden states and
corresponding emission probabilities plus initial probabilities of hidden
states.
How to use learned model to predict FUTURE values?
If we use sample() method it'll choose randomly initial state and will
generate some data. But it'll be just a random sample not a prediction of
FUTURE values.
Could please someone explain me how to predict future values?
BTW: I tried to model simple sin() signal and generate samples but
generated data doesn't resemble sin signal at all. Maybe it's because
transition matrix is symmetric.
One more question - "Is it possible to capture the behaviour of simple sin
wave and draw reasonable prediction of future values? "
--
Best regards,
Alex
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