
AutoOut: Automated Outlier Detection and Treatment Tool - kailashahirwar1
https://github.com/MateLabs/AutoOut
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nxpnsv
Dangerously opaque tool. You should tell users why a row is an outlier, and
you shoul document the methods you use (even if it’s just links to sklearn).
Also would be more valuable as a cli app

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je42
[https://github.com/MateLabs/AutoOut/blob/9c3b1f4195aa96e829c...](https://github.com/MateLabs/AutoOut/blob/9c3b1f4195aa96e829cdcde09b688090bac11cc6/app/outlier_treatment/spaces.py)

Looks like it applies multiple algos:

{"model": "zscore", "params": {"threshold":3.5}}, {"model": "DBSCAN",
"params": {}}, {"model": "OPTICS", "params": {}}, {"model": "IsolationForest",
"params": {}}, {"model": "EllipticEnvelope", "params": {}}, {"model":
"OneClassSVM", "params": {}}, {"model": "LocalOutlierFactor", "params": {}},

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stewbrew
"AutoOut is an automated outlier detection and treatment tool that allows you
to get better models with even better accuracy without writing a single line
of code."

Is this ironic? If not, shouldn't you somehow describe your method (including
references) for how to detect and "treat" outliers?

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kyberias
Seems like a simple tool that takes data files and tells about outliers. Why
does it have to be used with a web browser? If one runs it locally, it
probably should primarily have a command line interface.

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TrackerFF
So I just glanced over the code, or more specifically
[https://github.com/MateLabs/AutoOut/blob/master/app/outlier_...](https://github.com/MateLabs/AutoOut/blob/master/app/outlier_treatment/main.py)
\- and from what I can see, this is some kind of ensemble (learning) method
which votes out the predicted outliers?

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pw6hv
Agree with the comments below. I understand that the tool might be created
with statistics-illiterate people in mind as users, but as now it is on the
first page of Hacker News page we would expect a bit more details.

