TX-Means | free clustering algorithm

by riccotti Python Version: Current License: GPL-3.0

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kandi X-RAY | TX-Means Summary

TX-Means is a Python library. TX-Means has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However TX-Means build file is not available. You can download it from GitHub.

TX-Means is a parameter-free clustering algorithm able to efficiently partitioning transactional data in a completely automatic way. TX-Means is designed for the case where clustering must be applied on a massive number of different datasets, for instance when a large set of users need to be analyzed individually and each of them has generated a long history of transactions. In this repository we provide the source code of TX-Means, the clustering algorithm competitors and the dataset used in. Riccardo Guidotti, Anna Monreale, Mirco Nanni, Fosca Giannotti, Dino Pedreschi "Clustering Individual Transactional Data for Masses of Users", KDD 2017, 2017, Halifax, NS, Canada. Please cite the paper above if you use our code or dataets.

Support

Quality

Security

License

Reuse

Support

TX-Means has a low active ecosystem.

It has 14 star(s) with 6 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of TX-Means is current.

Quality

TX-Means has 0 bugs and 0 code smells.

Security

TX-Means has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

TX-Means code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

TX-Means is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

TX-Means releases are not available. You will need to build from source code and install.

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

It has 2430 lines of code, 124 functions and 14 files.

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

Top functions reviewed by kandi - BETA

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

Perform clustering
Stabilizes clusters
Partition the cluster
Update cluster info
Fit the model
Find medioids based on jaccard clustering
Calculate the Jacobian distance between two points
Assigns all sheets to centroids
Run the clustering algorithm
Calculates the frequency for each item in the basket
Perform the iteration of the algorithm
Convert a bitarray to a list
Remap items from a list
Calculates the weighted quality of a basket
Calculate the quality of a basket
Calculate purity
Count the number of items in a basket
Convert a list of basket objects to bitarray
Calculate the weighted lisr of a list of lists
Compute the weighted entropy of a list of sheets
Calculate the weighted weight of a list
Calculate the aggregated measures
Compute silhouette score
Read UCI data from a CSV file
Performs clustering
Estimate the clustering

Get all kandi verified functions for this library.

TX-Means Key Features

No Key Features are available at this moment for TX-Means.

TX-Means Examples and Code Snippets

No Code Snippets are available at this moment for TX-Means.

Community Discussions

No Community Discussions are available at this moment for TX-Means.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install TX-Means

You can download it from GitHub.
You can use TX-Means 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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