Hey everybody 
I am working with the example on
Everything worked fine so far…I could reproduce a result, that was quite similar to the one Matt showed on YouTube (https://www.youtube.com/watch?v=S-0thrzOHTc). 
Now I wanted to investigate the influence, the swarming has on the result.
So I ran a swarm with “swarmSize”: “large”
Now I did the Prediction with the resulting model_params.
And actually… I think it looks too good… Like an over fitting. 
Here one can see (a part of) the result:
The Prediction and the Data are most of the time exactly the same (just sometimes there is a little difference).
Now my question: is this normal when working with a large swarm? Is this the reason why we normally take a medium one?
Thank you all very much in advance for your help 
1 Like
Did you compare the model params the large swarm returned vs the medium? there may not be much of a different. A large swarm sometimes won’t even help much.
Also, if you are plotting the data, you want to use the inference shifter to align the predictions with the observations. If predictions are trailing exactly one time step behind observations, it means the system does not have a valid prediction, so it will simply return the value it just observed.
2 Likes
sooo first sorry for the late reply.
I was super sick the last 2 weeks.
ok I just misunderstood the thing with the shift. Super big sorry for that.
Anyway, I just ran the large swarm again and afterwards the prediction with the MODEL_PARAMS from the large swarm. And finally it worked. 
I don’t know what happened last time. 
Soo, thank you very much for the help
2 Likes
