pyswarms | research toolkit for particle swarm optimization | Machine Learning library

by ljvmiranda921 Python Version: 1.3.0 License: MIT

X-Ray Key Features Code Snippets(4)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | pyswarms Summary

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

PySwarms is an extensible research toolkit for particle swarm optimization (PSO) in Python.

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Quality

Security

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Support

pyswarms has a medium active ecosystem.

It has 1080 star(s) with 317 fork(s). There are 36 watchers for this library.

It had no major release in the last 12 months.

There are 19 open issues and 198 have been closed. On average issues are closed in 141 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pyswarms is 1.3.0

Quality

pyswarms has 0 bugs and 0 code smells.

Security

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

pyswarms code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pyswarms 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

pyswarms releases are available to install and integrate.

Deployable package is available in PyPI.

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

Installation instructions, examples and code snippets are available.

pyswarms saves you 1506 person hours of effort in developing the same functionality from scratch.

It has 3559 lines of code, 320 functions and 79 files.

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

Top functions reviewed by kandi - BETA

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

Shrink the memory
Calculate out bounds for bounds
R Compute the best solution for a given topology
Compute the neighbors of a swarm
Compute velocity of a swarm
Compute the velocity of a swarm
Compute velocity
Return a new position reflecting the given position
Make periodic periodic boundary
Calculate intermediate position
Invert velocity
Clamp velocity
Calculate the best - neighbor divergence
Calculate the Vonannoy correlation coefficient
Adjust velocity
Generate a random position
Compute the position of the given swarm
Compute the position of a swarm
Compute the position within a bounding box
Computes the position of a given swarm
Computes the position of the given swarm
Setup the logger
Converts velocity to zero
Unmodified velocity

Get all kandi verified functions for this library.

pyswarms Key Features

No Key Features are available at this moment for pyswarms.

pyswarms Examples and Code Snippets

Is there any way to choose how many features are selected in Binary Particle Swarm Optimization?

Python

Lines of Code : 17

License : Strong Copyleft (CC BY-SA 4.0)

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    # Perform classification and store performance in P
    classifier.fit(X_subset, y)
    P = (classifier.predict(X_subset) == y).mean()
    # Compute for the objective function
    j = (alpha * (1.0 - P)
        + (1.0 - alpha) * (1 - (

Variable scope is changed in consecutive cells using %%time in Jupyter notebook

Python

Lines of Code : 22

License : Strong Copyleft (CC BY-SA 4.0)

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Python 3.7.2 | packaged by conda-forge | (default, Mar 19 2019, 20:46:22)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.4.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: foo = "bar"

In [2]: foo
O

Particle position not being parametrized properly in pyswarms

Python

Lines of Code : 71

License : Strong Copyleft (CC BY-SA 4.0)

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  [...]
  File "C:\FILES\boates\Anaconda\envs\warping_pso_dbscan\lib\site-packages\sklearn\cluster\dbscan_.py", line 139, in dbscan
    if not eps > 0.0:
ValueError: The truth value of an array with more than one element is ambiguous. U

MatPlotLib won't install without python 3.5 or above and pip 18 and above, and I don't have root access

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

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pip install pyswarms 'matplotlib<3.0'

Community Discussions

Trending Discussions on pyswarms

Is there any way to choose how many features are selected in Binary Particle Swarm Optimization?

QUESTION

Is there any way to choose how many features are selected in Binary Particle Swarm Optimization?

Asked 2021-Mar-16 at 11:36

I implemented BPSO as a feature selection approach using the pyswarms library. I followed this tutorial.

Is there a way to limit the maximum number of features? If not, are there other particle swarm (or genetic/simulated annealing) python-implementations that have this functionality?

...

ANSWER

Answered 2021-Mar-16 at 11:36

An easy way is to introduce a penalty for using any number of features. The in the following code a objective i defined

Source https://stackoverflow.com/questions/66651926

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

Vulnerabilities

No vulnerabilities reported

Install pyswarms

To install PySwarms, run this command in your terminal:. This is the preferred method to install PySwarms, as it will always install the most recent stable release.