sporco
zoofs
| sporco | zoofs | |
|---|---|---|
| 1 | 4 | |
| 250 | 236 | |
| - | - | |
| 3.9 | 0.0 | |
| 16 days ago | 5 months ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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sporco
zoofs
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[D] Feature engineering automation?
and as u described considering you will end up with a lot of features. https://github.com/jaswinder9051998/zoofs for feature selection. Zoofs is a wrapper based feature selection, so you'll be able select feature-based purely on performance if u have a healthy test set or if u perform cross-validation
- [P] Feature Selection for tabular data (Zoofs, python package)
- Zoofs, a feature selection Library
- Zoofs , nature inspired wrapper algorithms
What are some alternatives?
xtensor-signal - Signal processing features based on xtensor
scikit-opt - Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
biteopt - Derivative-Free Global Optimization Method (C++, Python binding)
Sklearn-genetic-opt - ML hyperparameters tuning and features selection, using evolutionary algorithms.
Parameterize.Net - Parameterize.Net is a library that allows developers to represent complex objects using float array.
GARI - GARI (Genetic Algorithm for Reproducing Images) reproduces a single image using Genetic Algorithm (GA) by evolving pixel values.
deeplearning
NitroFE - NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.
TorchGA - Train PyTorch Models using the Genetic Algorithm with PyGAD
GeneticAlgorithmPython - Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
PSOClustering - This is an implementation of clustering IRIS dataset with particle swarm optimization(PSO)
RocketLander - A simple framework equipped with optimization algorithms, such as reinforcement learning, evolution strategies, genetic optimization, and simulated annealing, to enable an orbital rocket booster to land autonomously.