Open nipunbatra opened 7 years ago
Is this what you mean? The correlation between static factors and the HVAC energy consumption.
This is the first step. Next:
Do a scatter between HVAC energy and static features. This is to see if a few outliers are causing low correlation
This is the result I got by scattering HVAC energy and static features. For this,
Pass each of these static factors to learn_HAT one at a time. Keep a=2. This way, we have one fixed latent factor for H and one will be learned. Since correlation with static factors is low, we would hope to see that the corresponding latent factor for appliance would be close to 0.
About the second one, I am not sure if I understand it correctly. I just draw a figure for the tensor decomposition blew.
I am not sure about the "corresponding latent factor" you mentioned. Based on the decomposition, I think we need to consider the factors learned in tensor A and matrix T to check if the static factors was related with the consumption or not. Is my understanding correct?
Thanks!
Yes. That's right.
I did experiments you mentioned before and got the results:
Why: We observed that the HVAC performance for Tensor factorisation becomes worse (CASE 2) when we add in the static features. Why is it so?
How: We will look into the correlation between static factors and the HVAC energy consumption. If this correlation is close to 0, the learnt latent factors should be 0 to ensure these features don't contribute. Is this the case?