
Anomalyzer – An Anomaly Detection Package - schmichael
http://www.getlytics.com/blog/post/check_out_anomalyzer
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alexforster
I'm not a statistician, which is why I really like this kind of approach. It
feels "FiveThirtyEight" trustworthy to me – a weighted average of different
opinions.

The claim that it "dynamically adjusts the weight of each algorithm according
to the amount of information it contains" is a bit hyperbolic, though. The
"weight" function is explained in the code this way:

"If either the "magnitude" [or] "fence" methods don't have any probability to
contribute, we don't want to hear about it. If they do, we upweight them
substantially."

Regardless, this is unquestionably a great foundation to build into your own
systems. Perhaps not as turn-key as the blog suggests, but still a wonderful
contribution.

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boltzmannbrain
Has anyone played with Anomalyzer yet? I'd like to get the anomaly probability
for every data instance of a CSV but it's unclear to me if this is possible. I
want to run it on the Numenta Anomaly Benchmark dataset
([https://github.com/numenta/NAB](https://github.com/numenta/NAB)) to see how
it compares to other anomaly detection algorithms.

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huac
Looking at your examples, seems like this is a changepoint package more than
anomaly detection.

There's a fair amount of user input here (still) - picking weights and
thresholds is a nontrivial task.

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drewlanenga
Fair point.

If you're interested in the changepoint detection use cases, we have a package
for that, too. :)

[https://github.com/lytics/impact](https://github.com/lytics/impact)

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hlfw0rd
Super cool. Now I can organize a statistical hierarchy of anomalies and assign
to appropriate workers!

~~~
0xdeadbeefbabe
You could also set up a statistical hierarchy of workers to blame for you
anomalies.

~~~
hlfw0rd
touché

