kneed | Knee point detection in Python chart_with_upwards_trend | Machine Learning library

by arvkevi Python Version: 0.8.5 License: BSD-3-Clause

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | kneed Summary

kneed is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Numpy applications. kneed has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However kneed build file is not available. You can install using 'pip install kneed' or download it from GitHub, PyPI.

Knee-point detection in Python. This repository is an attempt to implement the kneedle algorithm, published here. Given a set of x and y values, kneed will return the knee point of the function. The knee point is the point of maximum curvature.

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Quality

Security

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Support

kneed has a low active ecosystem.

It has 596 star(s) with 70 fork(s). There are 10 watchers for this library.

There were 2 major release(s) in the last 12 months.

There are 6 open issues and 46 have been closed. On average issues are closed in 88 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of kneed is 0.8.5

Quality

kneed has 0 bugs and 0 code smells.

Security

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

kneed code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

kneed is licensed under the BSD-3-Clause License. This license is Permissive.

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

Reuse

kneed releases are available to install and integrate.

Deployable package is available in PyPI.

kneed has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

kneed saves you 353 person hours of effort in developing the same functionality from scratch.

It has 843 lines of code, 46 functions and 7 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Initialize objective function .
Generate bumpy .
Find the knee in the difference curve .
Plot the normalized knee .
Plot the knee .
Find the shape of x and y .
Randomly sample a Gaussian distribution .
Concatenate increasing range .
Concatenate decay .

Get all kandi verified functions for this library.

kneed Key Features

No Key Features are available at this moment for kneed.

kneed Examples and Code Snippets

No Code Snippets are available at this moment for kneed.

Community Discussions

Trending Discussions on kneed

How can I select the right ListBox Item automatically when I press the Button in the Item I want to Check to delete this Item?

How to install optional components (anaconda, jupyter) in custom dataproc image

Trouble installing turbodbc

Plot specific element values in matplotlib

QUESTION

How can I select the right ListBox Item automatically when I press the Button in the Item I want to Check to delete this Item?

Asked 2021-Jul-07 at 11:44

So I got in WPF an ListBox where I got an Button in my ListBoxItem through an DataTemplate. Im adding that Button Like this to my Item:

...

ANSWER

Answered 2021-Jul-07 at 11:44

In RemoveMark_Click the first argument (typically called sender and of type object) should by the Button you clicked on, and its DataContext should be your collection item to remove.

So change RemoveMark_Click to sth like:

Source https://stackoverflow.com/questions/68284752

QUESTION

How to install optional components (anaconda, jupyter) in custom dataproc image

Asked 2021-May-03 at 20:41

To speed up my cluster instantiation time, I've created a custom image with all the additional dependencies installed using miniconda3 available for dataproc image 1.5.34-debian10. (I followed the steps here: GCP Dataproc custom image Python environment to ensure I used the correct python environment).

However, when I start my cluster with --optional-components ANACONDA,JUPYTER my custom dependencies are removed and I'm left with a base installation of anaconda and jupyter. I assume the anaconda installation is overwriting my custom dependencies. Is there any way to ensure my dependencies aren't overwritten? If not, is it possible to install anaconda and jupyter as part of my custom dataproc image instead?

I've used the following command to create the custom image:

...

ANSWER

Answered 2021-May-03 at 20:41

The customize_conda.sh script is the recommended way of customizing Conda env for custom images.

If you need more than the script does, you can read the code and create your own script, but anyway you want to use the absolute path e.g., /opt/conda/anaconda/bin/conda, /opt/conda/anaconda/bin/pip, /opt/conda/miniconda3/bin/conda, /opt/conda/miniconda3/bin/pip to install/uninstall packages for the Anaconda/Miniconda env.

Source https://stackoverflow.com/questions/67357670

QUESTION

Trouble installing turbodbc

Asked 2021-Jan-11 at 20:49

I am attempting to install turbodbc on my Ubuntu 20.10 machine.
My specs are as follows: pip 20.2.4, Python 3.8.5 , gcc (Ubuntu 10.2.0-13ubuntu1) 10.2.0

I have attempted the solutions provided in the previous posts here and and here.

I am getting this error message

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ANSWER

Answered 2021-Jan-11 at 20:49

Boost is not installed. You can try this

Source https://stackoverflow.com/questions/65674126

QUESTION

Plot specific element values in matplotlib

Asked 2020-Nov-24 at 17:35

I have a list as below:

...

ANSWER

Answered 2020-Nov-24 at 17:35

You might think that everybody knows this library kneed. Well, I don't know about others but I have never seen that one before (it does not even have a tag here on SO).
But their documentation is excellent (qhull take note!). So, you could do something like this:

Source https://stackoverflow.com/questions/64989323

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