graforvfl package

• graforvfl.network package
  • graforvfl.network.base_rvfl module
    • BaseRVFL
      • BaseRVFL.weights
      • BaseRVFL.act_func
      • BaseRVFL.size_input
      • BaseRVFL.size_output
      • BaseRVFL.loss_train
      • BaseRVFL.CLS_OBJ_LOSSES
      • BaseRVFL.SUPPORTED_ACTIVATION
      • BaseRVFL.SUPPORTED_CLS_METRICS
      • BaseRVFL.SUPPORTED_REG_METRICS
      • BaseRVFL.SUPPORTED_WEIGHT_INITIALIZER
      • BaseRVFL.evaluate()
      • BaseRVFL.fit()
      • BaseRVFL.get_weights()
      • BaseRVFL.get_weights_size()
      • BaseRVFL.load_model()
      • BaseRVFL.partial_fit()
      • BaseRVFL.predict()
      • BaseRVFL.save_loss_train()
      • BaseRVFL.save_metrics()
      • BaseRVFL.save_model()
      • BaseRVFL.save_y_predicted()
      • BaseRVFL.score()
      • BaseRVFL.scores()
      • BaseRVFL.set_weights()
  • graforvfl.network.gfo_rvfl_comparator module
    • GfoRvflComparator
      • GfoRvflComparator.problem_type
      • GfoRvflComparator.bounds
      • GfoRvflComparator.optim_list
      • GfoRvflComparator.optim_params_list
      • GfoRvflComparator.scoring
      • GfoRvflComparator.cv
      • GfoRvflComparator.seed
      • GfoRvflComparator.verbose
      • GfoRvflComparator.mode
      • GfoRvflComparator.n_workers
      • GfoRvflComparator.termination
      • GfoRvflComparator.kwargs
      • GfoRvflComparator.plot_average_runtime()
      • GfoRvflComparator.plot_loss_train_average()
      • GfoRvflComparator.plot_loss_train_per_trial()
      • GfoRvflComparator.plot_metric_boxplot()
      • GfoRvflComparator.run()
  • graforvfl.network.gfo_rvfl_cv module
    • GfoRvflCV
      • GfoRvflCV.SUPPORTED_CLS_METRICS
      • GfoRvflCV.SUPPORTED_REG_METRICS
      • GfoRvflCV.evaluate()
      • GfoRvflCV.fit()
      • GfoRvflCV.load_model()
      • GfoRvflCV.predict()
      • GfoRvflCV.save_convergence()
      • GfoRvflCV.save_model()
      • GfoRvflCV.save_performance_metrics()
      • GfoRvflCV.save_y_predicted()
      • GfoRvflCV.score()
      • GfoRvflCV.scores()
    • HyperparameterProblem
      • HyperparameterProblem.obj_func()
  • graforvfl.network.gfo_rvfl_tuner module
    • GfoRvflTuner
      • GfoRvflTuner.best_optim_params
      • GfoRvflTuner.best_score
      • GfoRvflTuner.best_searcher
      • GfoRvflTuner.SUPPORTED_CLS_METRICS
      • GfoRvflTuner.SUPPORTED_REG_METRICS
      • GfoRvflTuner.fit()
      • GfoRvflTuner.predict()
      • GfoRvflTuner.score()
  • graforvfl.network.standard_rvfl module
    • RvflClassifier
      • RvflClassifier.CLS_OBJ_LOSSES
      • RvflClassifier.evaluate()
      • RvflClassifier.fit()
      • RvflClassifier.partial_fit()
      • RvflClassifier.predict()
      • RvflClassifier.predict_proba()
      • RvflClassifier.score()
      • RvflClassifier.scores()
      • RvflClassifier.set_partial_fit_request()
    • RvflRegressor
      • RvflRegressor.evaluate()
      • RvflRegressor.score()
      • RvflRegressor.scores()
• graforvfl.shared package
  • graforvfl.shared.activator module
    • Functions:
    • Aliases:
    • 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
      • Data.SUPPORT
      • Data.encode_label()
      • Data.scale()
      • Data.set_train_test()
      • Data.split_train_test()
    • DataTransformer
      • DataTransformer.SUPPORTED_SCALERS
      • DataTransformer.fit()
      • DataTransformer.inverse_transform()
      • DataTransformer.transform()
    • FeatureEngineering
      • FeatureEngineering.create_threshold_binary_features()
    • TimeSeriesDifferencer
      • TimeSeriesDifferencer.difference()
      • TimeSeriesDifferencer.inverse_difference()
  • 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
      • BoxCoxScaler.fit()
      • BoxCoxScaler.inverse_transform()
      • BoxCoxScaler.transform()
    • LabelEncoder
      • LabelEncoder.fit()
      • LabelEncoder.fit_transform()
      • LabelEncoder.inverse_transform()
      • LabelEncoder.transform()
    • Log1pScaler
      • Log1pScaler.fit()
      • Log1pScaler.inverse_transform()
      • Log1pScaler.transform()
    • LogeScaler
      • LogeScaler.fit()
      • LogeScaler.inverse_transform()
      • LogeScaler.transform()
    • ObjectiveScaler
      • ObjectiveScaler.inverse_transform()
      • ObjectiveScaler.transform()
    • OneHotEncoder
      • OneHotEncoder.categories_
      • OneHotEncoder.fit()
      • OneHotEncoder.fit_transform()
      • OneHotEncoder.inverse_transform()
      • OneHotEncoder.transform()
    • SinhArcSinhScaler
      • SinhArcSinhScaler.fit()
      • SinhArcSinhScaler.inverse_transform()
      • SinhArcSinhScaler.transform()
    • SqrtScaler
      • SqrtScaler.fit()
      • SqrtScaler.inverse_transform()
      • SqrtScaler.transform()
    • YeoJohnsonScaler
      • YeoJohnsonScaler.fit()
      • YeoJohnsonScaler.inverse_transform()
      • YeoJohnsonScaler.transform()
  • graforvfl.shared.scorer module
    • get_all_classification_metrics()
    • get_all_regression_metrics()
    • get_metric_sklearn()
    • get_metrics()