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cleanX Alternatives
Similar projects and alternatives to cleanX
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InfluxDB
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flask-graphql-boilerplate
a flask boilerplate to get you up and running. Packed with GraphQL and an authentication system out of the box.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better cleanX alternative or higher similarity.
cleanX reviews and mentions
Posts with mentions or reviews of cleanX.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-12-23.
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Looking for a minimal Conda package project
Unfortunately, it's not minimal, and is quite complicated, but it's the one I wrote, so I can answer your questions if you have any: https://github.com/drcandacemakedamoore/cleanX/tree/main/conda-pkg and https://github.com/drcandacemakedamoore/cleanX/blob/main/setup.py (the links are to Conda-specific setup). I also created Conda builds for few other projects (not written by me):
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Hope this helps someone
If you work with medical images you may be interested to look at https://github.com/drcandacemakedamoore/cleanX . It does data cleaning for chest X-rays (DICOM or JPEGs) and associated information.
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Hello r/DS, wanted to share a package
A few months ago I posted to the machine learning channel about a package I thought some might find helpful for radiology images. The package, cleanX, has since evolved, and I think it can be even more helpful, and to actual data science practitioners in general. While it began for chest X-rays, many sections are generalizable for tabular data linked to images. Enjoy!
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[D] How to find dissimilarities between sets of images?
I faced a similar issue on chest X-rays. You can see what I did already about it in the library cleanX, but to summarize for an initial idea I averaged all the images in each set, then subtracted. It won't tell you much, but it will point to areas where things are different- in the case of roads with an without tractors, it will show big differences on the roads (unless there is a difference in what surrounds the roads)
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cleaning data, especially chest X-rays, before algorithm creation
There is no machine learning. The algorithms are meant to clean up the data before you build any machine learning algorithms. There are several ways to predict non-Xray images. One is to compare them to a small average image of all the X-rays. Take a look at the code (https://github.com/drcandacemakedamoore/cleanX), and you will find a couple of others...
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[R] cleaning data, especially chest X-rays
An excellent suggestion. I have thought about how best to implement demonstrations, because when I ran my code over a few Kaggle datasets, I found problems in them as I show here, but to know if I caught ALL of them or even most of them would require examining every single image by hand. But maybe the answer is to show a machine learning training task with dirty and cleanX cleaned data to show it makes a difference. I'll try to get to it soon.
- Sunday Daily Thread: What's everyone working on this week?
- Generalising data cleaning, is it possible?
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Stats
Basic cleanX repo stats
10
24
0.0
over 1 year ago
drcandacemakedamoore/cleanX is an open source project licensed under GNU General Public License v3.0 only which is an OSI approved license.
The primary programming language of cleanX is Jupyter Notebook.
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