fuzzy_labeling_scRNA | Data Labeling library

by maxime-langevin Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | fuzzy_labeling_scRNA Summary

fuzzy_labeling_scRNA is a Python library typically used in Artificial Intelligence, Data Labeling applications. fuzzy_labeling_scRNA has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

fuzzy_labeling_scRNA

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Quality

Security

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Reuse

Support

fuzzy_labeling_scRNA has a low active ecosystem.

It has 7 star(s) with 0 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

fuzzy_labeling_scRNA has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of fuzzy_labeling_scRNA is current.

Quality

fuzzy_labeling_scRNA has no bugs reported.

Security

fuzzy_labeling_scRNA has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

fuzzy_labeling_scRNA is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

fuzzy_labeling_scRNA releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed fuzzy_labeling_scRNA and discovered the below as its top functions. This is intended to give you an instant insight into fuzzy_labeling_scRNA implemented functionality, and help decide if they suit your requirements.

Concatenate multiple datasets
Filters out genes that are subset of genes
Calculate local mean and variance from a matrix
Rearrange the categories
Perform forward computation
Logarithm of the binning function
The reconstruction loss function
Binary logarithm function
Performs the forward computation
Broadcast discrete labels
Show a spatial expression
Forward function for the model
Run all the benchmarks
Calculate the entropy batch mixing of a gene
Filter GeneExpression Dataset
Preprocess cortex data
Forward computation
Preprocess BrainLarge data
Extract the attributes from a matrix
Calculate the KL divergence
Concatenate the given tensor
Computes the weight of the input tensor
Compute the hierarchical hierarchical accuracy
Calculate sample rate
Calculate the sample rate for a given image
Compute the mmd objective function

Get all kandi verified functions for this library.

fuzzy_labeling_scRNA Key Features

No Key Features are available at this moment for fuzzy_labeling_scRNA.

fuzzy_labeling_scRNA Examples and Code Snippets

No Code Snippets are available at this moment for fuzzy_labeling_scRNA.

Community Discussions

Trending Discussions on Data Labeling

How can I do this split process in Python?

Replacing a character with a space and dividing the string into two words in R

Azure ML FileDataset registers, but cannot be accessed for Data Labeling project

QUESTION

How can I do this split process in Python?

Asked 2021-Dec-30 at 14:06

I'm trying to make a data labeling in a table, and I need to do it in such a way that, in each row, the index is repeated, however, that in each column there is another Enum class.

What I've done so far is make this representation with the same enumerator class.

A solution using the column separately as a list would also be possible. But what would be the best way to resolve this?

...

ANSWER

Answered 2021-Dec-30 at 13:57

Instead of using Enum you can use a dict mapping. You can avoid loops if you flatten your dataframe:

Source https://stackoverflow.com/questions/70532286

QUESTION

Replacing a character with a space and dividing the string into two words in R

Asked 2020-Nov-18 at 07:32

I have a dataframe that contains a column that includes strings separeted with semi-colons and it is followed by a space. But unfortunately in some of the strings there is a semi-colon that is not followed by a space.

In this case, This is what i'd like to do: If there is a space after the semi-colon we do not need a change. However if there are letters before and after the semi-colon, we should change semi-colon with space

i have this:

...

ANSWER

Answered 2020-Nov-16 at 07:24

Try something like:

Source https://stackoverflow.com/questions/64853962

QUESTION

Azure ML FileDataset registers, but cannot be accessed for Data Labeling project

Asked 2020-Oct-28 at 20:31

Objective: Generate a down-sampled FileDataset using random sampling from a larger FileDataset to be used in a Data Labeling project.

Details: I have a large FileDataset containing millions of images. Each filename contains details about the 'section' it was taken from. A section may contain thousands of images. I want to randomly select a specific number of sections and all the images associated with those sections. Then register the sample as a new dataset.

Please note that the code below is not a direct copy and paste as there are elements such as filepaths and variables that have been renamed for confidentiality reasons.

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ANSWER

Answered 2020-Oct-27 at 22:39

Is the data behind virtual network by any chance?

Source https://stackoverflow.com/questions/64546521

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install fuzzy_labeling_scRNA

You can download it from GitHub.
You can use fuzzy_labeling_scRNA like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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