Comparison between HTM and other methods for Time Series predictions




I have wrote my own implementation of HTM system and i think i might be ready to make a comparison with existing methods. What methods should i check for that comparison? Are any of them available in MATLAB toolbox, or in R?


That’s great! There are several possible techniques you can compare with. The classic one is ARIMA, which is available in R (and probably Matlab). You could also compare against TDNN or LSTM. See our paper [1] for more details. The code we used to implement the simulations is available here:

You’ll probably want to look into this subdirectory (includes R ARIMA scripts):


[1] Cui, Y., Ahmad, S., & Hawkins, J. (2016) Continuous online sequence learning with an unsupervised neural network model. Neural Comput., 28, 2474–2504.


I got a problem predicting 5 steps ahead in hotgym comparing with Arima model (for 5 steps ahead my implementation is closely to ARIMA results, and its quite bad).
What might have gone wrong?

For one step ahead i have :

Where MAPE metric for my HTM system is 40% higher than ARIMA.

While for 5 steps ahead:

MAPE is 5% higher.

I use 950 mini-columns, and 12 cells per column(because of system limitations).
Also i use same SDR classifier(with softmax function) with only change SDR length(column size = prediction steps).
I would appreciate any tip, or direction.


Are these two different models? If so, where do the model params differ?


Model’s parameters are same in both cases. But for 5 steps ahead i get these results. The only difference is as i mentioned above for SDR classifier. Is there any code-pseudocode for SDR classifier (and decoder) procedure? Maybe i am missing something, when prediction steps become > 1?


Do you need to change the SDR classifier at all? What happens when you don’t?


I got same bad results… Where should i focus for this issue?