Welcome to GrafoRVFL’s documentation!

GrafoRVFL is an open-source library in Python that employs gradient-free optimization ((GA, PSO, WOA, TLO, DE, …) to optimize Random Vector Functional Link Networks. It is entirely implemented based on Numpy and fully compatible with the interfaces of the Scikit-Learn library. With GrafoRVFL, you can fine-tune the hyper-parameters of network or optimize weights in the network using gradient-free optimizers.

• Free software: GNU General Public License (GPL) V3 license

• Provided Estimator: RvflRegressor, RvflClassifier, GfoRvflTuner

• Total Gradient Free based RVFL Regressor: > 200 Models

• Total Gradient Free based RVFL Classifier: > 200 Models

• Supported performance metrics: >= 67 (47 regressions and 20 classifications)

• Supported objective functions (as fitness functions or loss functions): >= 67 (47 regressions and 20 classifications)

• Documentation: https://graforvfl.readthedocs.io

• Python versions: >= 3.8.x

• Dependencies: numpy, scipy, scikit-learn, pandas, mealpy, permetrics

Quick Start:

• Installation
• Tutorials
  • Provided classes
  • DataTransformer class
  • Data class
  • Neural Network class
  • Supported functions in model object

Models API:

• graforvfl package
  • graforvfl.network package
    • graforvfl.network.base_rvfl module
      • BaseRVFL
    • graforvfl.network.gfo_rvfl_tuner module
      • GfoRvflTuner
      • HyperparameterProblem
    • graforvfl.network.standard_rvfl module
      • RvflClassifier
      • RvflRegressor
  • graforvfl.shared package
    • graforvfl.shared.activator module
      • celu()
      • elu()
      • gelu()
      • hard_shrink()
      • hard_sigmoid()
      • hard_swish()
      • hard_tanh()
      • leaky_relu()
      • log_sigmoid()
      • log_softmax()
      • mish()
      • none()
      • prelu()
      • relu()
      • rrelu()
      • selu()
      • sigmoid()
      • silu()
      • soft_plus()
      • soft_shrink()
      • soft_sign()
      • softmax()
      • softmin()
      • swish()
      • tanh()
      • tanh_shrink()
    • graforvfl.shared.boundary_controller module
      • check_bool()
      • check_float()
      • check_int()
      • check_str()
      • check_tuple_float()
      • check_tuple_int()
      • is_in_bound()
      • is_str_in_list()
    • graforvfl.shared.data_processor module
      • Data
      • DataTransformer
      • FeatureEngineering
      • TimeSeriesDifferencer
      • get_dataset()
    • graforvfl.shared.randomer module
      • get_correct_shape()
      • get_generator()
      • glorot_normal_initializer()
      • glorot_uniform_initializer()
      • he_normal_initializer()
      • he_uniform_initializer()
      • lecun_normal_initializer()
      • lecun_uniform_initializer()
      • orthogonal_initializer()
      • random_normal_initializer()
      • random_uniform_initializer()
    • graforvfl.shared.scaler module
      • BoxCoxScaler
      • LabelEncoder
      • Log1pScaler
      • LogeScaler
      • ObjectiveScaler
      • SinhArcSinhScaler
      • SqrtScaler
      • YeoJohnsonScaler
    • graforvfl.shared.scorer module
      • get_all_classification_metrics()
      • get_all_regression_metrics()
      • get_metrics()

Support:

• Citation Request
• Important links
• License

Indices and tables

• Index

• Module Index

• Search Page