XMeans | Parameter-free K-means clustering : X-means | Machine Learning library

by alex000kim Python Version: Current License: MIT

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kandi X-RAY | XMeans Summary

XMeans is a Python library typically used in Artificial Intelligence, Machine Learning applications. XMeans has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However XMeans build file is not available. You can download it from GitHub.

Implementation of XMeans algorithm based on Pelleg, Dan, and Andrew W. Moore. "X-means: Extending K-means with Efficient Estimation of the Number of Clusters." ICML. Vol. 1. 2000. See tests.py for usage examples.

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XMeans has a low active ecosystem.

It has 48 star(s) with 3 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of XMeans is current.

Quality

XMeans has 0 bugs and 13 code smells.

Security

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

XMeans code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

XMeans 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

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

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

XMeans saves you 36 person hours of effort in developing the same functionality from scratch.

It has 97 lines of code, 7 functions and 2 files.

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

Top functions reviewed by kandi - BETA

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

Calculate the k - th k - means clustering .
Fit KMeans clustering .
r Log - likelihood function
Initialize XMeans algorithm .

Get all kandi verified functions for this library.

XMeans Key Features

No Key Features are available at this moment for XMeans.

XMeans Examples and Code Snippets

No Code Snippets are available at this moment for XMeans.

Community Discussions

Trending Discussions on XMeans

pyclustering visualising xmeans when the matrix has more than three dimensions

QUESTION

pyclustering visualising xmeans when the matrix has more than three dimensions

Asked 2020-Nov-26 at 09:58

I'm trying to cluster and visualise some data with xmeans from the pyclustering lib. I copied the code directly from the example in the documentation,

...

ANSWER

Answered 2020-Nov-22 at 18:01

In line with the error that you got:

Only objects with size dimension 1 (1D plot), 2 (2D plot) or 3 (3D plot) can be displayed. For multi-dimensional data use 'cluster_visualizer_multidim'.

You have to use cluster_visualizer_multidim as it was mentioned. There is a documentation (pyclustering 0.10.1) with an example: https://pyclustering.github.io/docs/0.10.1/html/dc/d6b/classpyclustering_1_1cluster_1_1cluster__visualizer__multidim.html

For example, if you have a data (D > 3) and you want to display (x0, x1) and (x0, x2) then you can display it in the following way:

Source https://stackoverflow.com/questions/64776260

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

Vulnerabilities

No vulnerabilities reported

Install XMeans

You can download it from GitHub.
You can use XMeans 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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