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> Some comments/suggestions for the future:
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> 1. It could be useful to show the distributions of the individual feature spaces with the option to show the z-scores. It might be easier for someone …
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The example provided in timeseries_anomaly_detection.py is not working in practice, and the final result shows only the portion of the output with the expected behaviour, but it skips the part that is…
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Hi,
Great project! I was wondering if there's any interest in adding robust statistics methods to remove outliers or detect frequency jumps.
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## Summary
The current implementation of `Tokenizer` is slower than html5ever. I believe that it can become as fast as html5ever.
## The current benchmark results
From #59
Running on the M…
kkebo updated
2 months ago
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stack overflow discussion on the topic: https://stackoverflow.com/questions/1174984/how-to-efficiently-calculate-a-running-standard-deviation
that would allow us to detect "outliers" scientifically…
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I would need some help understanding the strategy behind this method. Are you first finding outlying voxels in each volume and then of those, deciding which outliers are outlying in time?
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1) Subset data to potentially useful features
2) Detect and remove outliers
4) Collapse data at EAS level
5) Create any potentially relevant features
6) Any other data cleaning and standardization…
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I've selected some data from ais_clean (albeit with some field names different) using a select statement, converted to a message stream (so it's an array of dic items and then tried to run outlier_det…
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Hi there,
instead of a fixed mito-percent cutoff that I have to set each time, does scanpy have some automated way of finding outliers of some heuristic to find a reasonable cutoff?
If not, do …