enstop | Ensemble topic modelling with pLSA | Topic Modeling library

by lmcinnes Python Version: 0.2.6 License: BSD-2-Clause

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | enstop Summary

enstop is a Python library typically used in Artificial Intelligence, Topic Modeling applications. enstop has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install enstop' or download it from GitHub, PyPI.

Ensemble topic modelling with pLSA

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Quality

Security

License

Reuse

Support

enstop has a low active ecosystem.

It has 97 star(s) with 12 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 6 open issues and 0 have been closed. On average issues are closed in 247 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of enstop is 0.2.6

Quality

enstop has 0 bugs and 0 code smells.

Security

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

enstop code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

enstop is licensed under the BSD-2-Clause License. This license is Permissive.

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

Reuse

enstop releases are available to install and integrate.

Deployable package is available in PyPI.

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

enstop saves you 727 person hours of effort in developing the same functionality from scratch.

It has 1678 lines of code, 60 functions and 6 files.

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

Top functions reviewed by kandi - BETA

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

Calculate the average coherence coefficient
Returns the intersection of two arrays
Compute the coherence coefficient
Calculate the Coherence coefficient
Calculate the log - lift log - likelihood
Calculate the log likelihood of a topic
Mean log - lift function
Logical log - likelihood
Apply transform to X
Calculate the log - likelihood
Refit the partitioning test
Perform the PLS optimization
Generate the combined combined topics
Computes the KL divergence between a and b
Compute the KL divergence of all pairs
Calculate Plsa - topic topics
Check the sample weight
Calculate NMF topics
Normalize a ndarray
Generate the combined topics heuristic
Calculate the hellinger distance between distributions
Fit the model
Wrapper for the log - likelihood function
Calculate the coherence coefficient
Calculate the log - likelihood of the model
Calculate the log - shift of the model

Get all kandi verified functions for this library.

enstop Key Features

No Key Features are available at this moment for enstop.

enstop Examples and Code Snippets

No Code Snippets are available at this moment for enstop.

Community Discussions

Trending Discussions on enstop

how to extract data from a code using python

QUESTION

how to extract data from a code using python

Asked 2018-Sep-30 at 19:32

I have some functions, as .txt files which are written using easy language and I need to extract data from those functions using python. as an example consider the following part.

code segment -

...

ANSWER

Answered 2018-Sep-30 at 19:19

Here is an example for finding and splitting the text between if and then The result is a list of the individual elements: variables, brackets and the comparison operators.

Source https://stackoverflow.com/questions/52538047

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

Vulnerabilities

No vulnerabilities reported

Install enstop

You can install using 'pip install enstop' or download it from GitHub, PyPI.
You can use enstop 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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