sklearn-genetic-opt

scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms.

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This is meant to be an alternative to popular methods inside scikit-learn such as Grid Search and Randomized Grid Search for hyperparameters tuning, and from RFE, Select From Model for feature selection.

Sklearn-genetic-opt uses evolutionary algorithms from the deap package to choose a set of hyperparameters that optimizes (max or min) the cross-validation scores, it can be used for both regression and classification problems.

Installation:

Install sklearn-genetic-opt

It’s advised to install sklearn-genetic using a virtual env, to install a light version, inside the env use:

pip install sklearn-genetic-opt

sklearn-genetic-opt requires:

• Python (>= 3.8)

• scikit-learn (>= 1.1.0)

• NumPy (>= 1.19.0)

• DEAP (>= 1.3.3)

• tqdm (>= 4.61.1)

Extra requirements:

These requirements are necessary to use plots, MLflowConfig and TensorBoard correspondingly.

• Seaborn (>= 0.11.2)

• MLflow (>= 1.30.0)

• Tensorflow (>= 2.0.0)

This command will install all the extra requirements:

pip install sklearn-genetic-opt[all]

User Guide / Tutorials:

• How to Use Sklearn-genetic-opt
• Using Callbacks
• Custom Callbacks
• Using Adapters
• Understanding the evaluation process
• Integrating with MLflow
• Reproducibility

Jupyter notebooks examples:

• Scikit-learn Comparison
• Pipeline Prediction
• Iris Feature Selection
• Digits Classification
• MLflow Logger
• Iris Multi-metric

Release Notes

• Release Notes
  • What’s new in 0.10.1
  • What’s new in 0.10.0
  • What’s new in 0.9.0
  • What’s new in 0.8.1
  • What’s new in 0.8.0
  • What’s new in 0.7.0
  • What’s new in 0.6.1
  • What’s new in 0.6.0
  • What’s new in 0.5.0
  • What’s new in 0.4.1
  • What’s new in 0.4
  • What’s new in 0.3
  • What’s new in 0.2
  • What’s new in 0.1

API Reference:

• GASearchCV
  • GASearchCV
• GAFeatureSelectionCV
  • GAFeatureSelectionCV
• Callbacks
  • BaseCallback
  • ProgressBar
  • ConsecutiveStopping
  • DeltaThreshold
  • TimerStopping
  • ThresholdStopping
  • TensorBoard
  • LogbookSaver
• Schedules
  • BaseAdapter
  • ConstantAdapter
  • ExponentialAdapter
  • InverseAdapter
  • PotentialAdapter
• Plots
  • plot_fitness_evolution()
  • plot_search_space()
• MLflow
  • MLflowConfig
• Space
  • Categorical
  • Continuous
  • Integer
  • Space
• Algorithms
  • eaMuCommaLambda()
  • eaMuPlusLambda()
  • eaSimple()

External References:

• Articles
• Contributing

Indices and tables

• Index

• Module Index

• Search Page