# Feedback on network setup for anomaly detection

**URL:** <https://discourse.numenta.org/t/feedback-on-network-setup-for-anomaly-detection/2778>\
**Category:** HTM.Java\
**Tags:** anomaly-detection, network\
**Created:** [September 5, 2017, 11:15am UTC](https://discourse.numenta.org/t/feedback-on-network-setup-for-anomaly-detection/2778 "2017-09-05T11:15:37Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![Andrea\_Giordano](https://avatars.discourse-cdn.com/v4/letter/a/ed8c4c/32.png) [@Andrea\_Giordano](https://discourse.numenta.org/u/Andrea_Giordano)\
**Post date:** [September 5, 2017, 4:47pm UTC](https://discourse.numenta.org/t/feedback-on-network-setup-for-anomaly-detection/2778/2 "2017-09-05T16:47:26Z")

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I tried to play a bit with parameters, especially with resolution, n and w ones. My goal is also to obtain prediction values together with anomaly scores.

Reading at [htm post](https://discourse.numenta.org/t/is-my-data-being-predicted-correctly/735/10) it seems that n should be 300-400 while w around 21.  
Moreover, about resolution, focusing on my data probably a better choice would be 0.01 instead of 0.1.

So using those probably I fits better my dataset obtaining higher anomaly scores. I’ve also noticed that n = 400 make the algorithm a bit slow. Which are the criteria to choose n and w?

In order to obtain also predicted values I printed also:  
`getClassification("read").getMostProbableValues(1)`  
but I obtain very strange values… sometimes null for example, sometimes already the same fixed value.

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