SwarmML
A python package that utilizes Particle Swarm Optimization for Feature Selection
SwarmML is a Python package that implements Particle Swarm Optimization (PSO) for feature selection. It can be used to improve the performance of classification and regression tasks by automatically selecting the most informative features from a given dataset.
Features
- Performs feature selection using Particle Swarm Optimization.
- Supports both classification and regression tasks.
- Provides customizable parameters for PSO algorithm.
- Simple and easy to use package.
Installation
You can install SwarmML using pip:
pip install SwarmML
Examples
Example 1
import SwarmML
from sklearn.datasets import load_iris
X,Y = load_iris(return_X_y=True)
obj = SwarmML.FeatureSelection.Particle_Swarm_Optimization('Classification')
Best_Features, Best_Score = obj.run(X, Y)
1 maintainer
Metadata
1 maintainer
Release files for SwarmML 1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| SwarmML-1.0.tar.gz | 4.9 kB | Without provenance | Details for SwarmML-1.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| SwarmML-1.0-py3-none-any.whl | Python 3 | none | any | Details for SwarmML-1.0-py3-none-any.whl |
Total release size: 10.4 kB
Release files / SwarmML-1.0.tar.gz
| Download URL | SwarmML-1.0.tar.gz |
|---|---|
| Size | 4.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / SwarmML-1.0-py3-none-any.whl
| Download URL | SwarmML-1.0-py3-none-any.whl |
|---|---|
| Size | 5.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.6
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Security for SwarmML 1.0
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