Index

_

_fit() (waveletml.models.mha_wnn.BaseMhaWnnModel method) _process_data() (waveletml.models.gd_wnn.BaseGdWnnModel method) (waveletml.models.gd_wnn.GdWnnClassifier method) (waveletml.models.gd_wnn.GdWnnRegressor method)

_set_lb_ub() (waveletml.models.mha_wnn.BaseMhaWnnModel method) _set_optimizer() (waveletml.models.mha_wnn.BaseMhaWnnModel method) _train() (waveletml.models.gd_wnn.BaseGdWnnModel method)

A

act_output (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute)

B

BaseCallback (class in waveletml.helpers.callbacks) BaseCustomWNN (class in waveletml.models.custom_wnn) BaseGdWnnModel (class in waveletml.models.gd_wnn) BaseMhaWnnModel (class in waveletml.models.mha_wnn) BaseModel (class in waveletml.models.base_model)

batch_size (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) BoxCoxScaler (class in waveletml.helpers.data_scaler) build_model() (waveletml.models.mha_wnn.BaseMhaWnnModel method), [1]

C

callbacks (waveletml.models.gd_wnn.BaseGdWnnModel attribute) categories_ (waveletml.helpers.data_scaler.OneHotEncoder attribute) centers (waveletml.helpers.wavelet_layers.WaveletExpansionLayer attribute) (waveletml.helpers.wavelet_layers.WaveletProductLayer attribute) (waveletml.helpers.wavelet_layers.WaveletSummationLayer attribute) (waveletml.helpers.wavelet_layers.WaveletWeightedLinearLayer attribute) check_bool() (in module waveletml.helpers.verifier) check_float() (in module waveletml.helpers.verifier) check_int() (in module waveletml.helpers.verifier) check_str() (in module waveletml.helpers.verifier)

check_tuple_float() (in module waveletml.helpers.verifier) check_tuple_int() (in module waveletml.helpers.verifier) classes_ (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.mha_wnn.MhaWnnClassifier attribute) create_threshold_binary_features() (waveletml.helpers.data_preparer.FeatureEngineering method) criterion (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) CustomWaveletExpansionNetwork (class in waveletml.models.custom_wnn) CustomWaveletProductNetwork (class in waveletml.models.custom_wnn) CustomWaveletSummationNetwork (class in waveletml.models.custom_wnn) CustomWaveletWeightedLinearNetwork (class in waveletml.models.custom_wnn)

D

Data (class in waveletml.helpers.data_preparer) data (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) DataTransformer (class in waveletml.helpers.data_preparer)

device (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) difference() (waveletml.helpers.data_preparer.TimeSeriesDifferencer method)

E

EarlyStoppingCallback (class in waveletml.helpers.callbacks) encode_label() (waveletml.helpers.data_preparer.Data static method) epochs (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute)

evaluate() (waveletml.models.base_model.BaseModel method) (waveletml.models.gd_wnn.GdWnnClassifier method), [1] (waveletml.models.gd_wnn.GdWnnRegressor method), [1] (waveletml.models.mha_wnn.MhaWnnClassifier method), [1] (waveletml.models.mha_wnn.MhaWnnRegressor method), [1]

F

FeatureEngineering (class in waveletml.helpers.data_preparer) FileLoggerCallback (class in waveletml.helpers.callbacks) fit() (waveletml.helpers.data_preparer.DataTransformer method) (waveletml.helpers.data_scaler.BoxCoxScaler method) (waveletml.helpers.data_scaler.LabelEncoder method) (waveletml.helpers.data_scaler.Log1pScaler method) (waveletml.helpers.data_scaler.LogeScaler method) (waveletml.helpers.data_scaler.OneHotEncoder method) (waveletml.helpers.data_scaler.SinhArcSinhScaler method) (waveletml.helpers.data_scaler.SqrtScaler method) (waveletml.helpers.data_scaler.YeoJohnsonScaler method) (waveletml.models.base_model.BaseModel method) (waveletml.models.gd_wnn.GdWnnClassifier method), [1] (waveletml.models.gd_wnn.GdWnnRegressor method), [1] (waveletml.models.mha_wnn.MhaWnnClassifier method), [1] (waveletml.models.mha_wnn.MhaWnnRegressor method), [1]

fit_transform() (waveletml.helpers.data_scaler.LabelEncoder method) (waveletml.helpers.data_scaler.OneHotEncoder method) forward() (waveletml.helpers.wavelet_layers.WaveletExpansionLayer method), [1] (waveletml.helpers.wavelet_layers.WaveletProductLayer method), [1] (waveletml.helpers.wavelet_layers.WaveletSummationLayer method), [1] (waveletml.helpers.wavelet_layers.WaveletWeightedLinearLayer method), [1] (waveletml.models.custom_wnn.BaseCustomWNN method) (waveletml.models.custom_wnn.CustomWaveletExpansionNetwork method), [1] (waveletml.models.custom_wnn.CustomWaveletProductNetwork method), [1] (waveletml.models.custom_wnn.CustomWaveletSummationNetwork method), [1] (waveletml.models.custom_wnn.CustomWaveletWeightedLinearNetwork method), [1]

G

GdWnnClassifier (class in waveletml.models.gd_wnn) GdWnnRegressor (class in waveletml.models.gd_wnn) get_all_classification_metrics() (in module waveletml.helpers.evaluator) get_all_regression_metrics() (in module waveletml.helpers.evaluator)

get_metric_sklearn() (in module waveletml.helpers.evaluator) get_metrics() (in module waveletml.helpers.evaluator) get_name() (waveletml.models.mha_wnn.BaseMhaWnnModel method), [1] get_weights() (waveletml.models.custom_wnn.BaseCustomWNN method) get_weights_size() (waveletml.models.custom_wnn.BaseCustomWNN method)

H

haar() (in module waveletml.helpers.wavelet_funcs)

I

in_features (waveletml.helpers.wavelet_layers.WaveletExpansionLayer attribute) input_dim (waveletml.helpers.wavelet_layers.WaveletProductLayer attribute) (waveletml.helpers.wavelet_layers.WaveletSummationLayer attribute) (waveletml.helpers.wavelet_layers.WaveletWeightedLinearLayer attribute) inverse_difference() (waveletml.helpers.data_preparer.TimeSeriesDifferencer method) inverse_transform() (waveletml.helpers.data_preparer.DataTransformer method) (waveletml.helpers.data_scaler.BoxCoxScaler method) (waveletml.helpers.data_scaler.LabelEncoder method) (waveletml.helpers.data_scaler.Log1pScaler method) (waveletml.helpers.data_scaler.LogeScaler method) (waveletml.helpers.data_scaler.ObjectiveScaler method) (waveletml.helpers.data_scaler.OneHotEncoder method) (waveletml.helpers.data_scaler.SinhArcSinhScaler method) (waveletml.helpers.data_scaler.SqrtScaler method) (waveletml.helpers.data_scaler.YeoJohnsonScaler method)

is_in_bound() (in module waveletml.helpers.verifier) is_str_in_list() (in module waveletml.helpers.verifier)

K

kwargs (waveletml.models.gd_wnn.BaseGdWnnModel attribute)

L

LabelEncoder (class in waveletml.helpers.data_scaler) load_model() (waveletml.models.base_model.BaseModel static method) Log1pScaler (class in waveletml.helpers.data_scaler) LogeScaler (class in waveletml.helpers.data_scaler)

loss_train (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) (waveletml.models.mha_wnn.MhaWnnClassifier attribute) (waveletml.models.mha_wnn.MhaWnnRegressor attribute)

M

metric_class (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) (waveletml.models.mha_wnn.MhaWnnClassifier attribute) (waveletml.models.mha_wnn.MhaWnnRegressor attribute) mexican_hat() (in module waveletml.helpers.wavelet_funcs) MhaWnnClassifier (class in waveletml.models.mha_wnn) MhaWnnRegressor (class in waveletml.models.mha_wnn) minmax (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) (waveletml.models.mha_wnn.MhaWnnClassifier attribute) (waveletml.models.mha_wnn.MhaWnnRegressor attribute) ModelCheckpointCallback (class in waveletml.helpers.callbacks) module waveletml.helpers.callbacks waveletml.helpers.data_preparer waveletml.helpers.data_scaler waveletml.helpers.evaluator waveletml.helpers.verifier waveletml.helpers.wavelet_funcs waveletml.helpers.wavelet_layers waveletml.models.base_model waveletml.models.custom_wnn waveletml.models.gd_wnn waveletml.models.mha_wnn

morlet() (in module waveletml.helpers.wavelet_funcs)

N

network (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) (waveletml.models.mha_wnn.MhaWnnClassifier attribute) (waveletml.models.mha_wnn.MhaWnnRegressor attribute)

num_neurons (waveletml.helpers.wavelet_layers.WaveletProductLayer attribute) (waveletml.helpers.wavelet_layers.WaveletSummationLayer attribute) (waveletml.helpers.wavelet_layers.WaveletWeightedLinearLayer attribute)

O

objective_function() (waveletml.models.mha_wnn.BaseMhaWnnModel method), [1] ObjectiveScaler (class in waveletml.helpers.data_scaler) on_batch_begin() (waveletml.helpers.callbacks.BaseCallback method) on_batch_end() (waveletml.helpers.callbacks.BaseCallback method) on_epoch_begin() (waveletml.helpers.callbacks.BaseCallback method) on_epoch_end() (waveletml.helpers.callbacks.BaseCallback method) (waveletml.helpers.callbacks.EarlyStoppingCallback method) (waveletml.helpers.callbacks.FileLoggerCallback method) (waveletml.helpers.callbacks.ModelCheckpointCallback method) (waveletml.helpers.callbacks.PrintLossCallback method) on_train_begin() (waveletml.helpers.callbacks.BaseCallback method) on_train_end() (waveletml.helpers.callbacks.BaseCallback method) (waveletml.helpers.callbacks.FileLoggerCallback method) OneHotEncoder (class in waveletml.helpers.data_scaler) optim (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute)

optim_params (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) optimizer (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) (waveletml.models.mha_wnn.MhaWnnClassifier attribute) (waveletml.models.mha_wnn.MhaWnnRegressor attribute) out_features (waveletml.helpers.wavelet_layers.WaveletExpansionLayer attribute) output_layer (waveletml.models.custom_wnn.CustomWaveletExpansionNetwork attribute) (waveletml.models.custom_wnn.CustomWaveletProductNetwork attribute) (waveletml.models.custom_wnn.CustomWaveletSummationNetwork attribute) (waveletml.models.custom_wnn.CustomWaveletWeightedLinearNetwork attribute)

P

predict() (waveletml.models.base_model.BaseModel method) (waveletml.models.gd_wnn.GdWnnClassifier method), [1] (waveletml.models.gd_wnn.GdWnnRegressor method), [1] (waveletml.models.mha_wnn.MhaWnnClassifier method), [1] (waveletml.models.mha_wnn.MhaWnnRegressor method), [1]

predict_proba() (waveletml.models.gd_wnn.GdWnnClassifier method), [1] (waveletml.models.mha_wnn.MhaWnnClassifier method), [1] PrintLossCallback (class in waveletml.helpers.callbacks)

S

save_evaluation_metrics() (waveletml.models.base_model.BaseModel method) save_model() (waveletml.models.base_model.BaseModel method) save_training_loss() (waveletml.models.base_model.BaseModel method) save_y_predicted() (waveletml.models.base_model.BaseModel method) scale() (waveletml.helpers.data_preparer.Data static method) scales (waveletml.helpers.wavelet_layers.WaveletExpansionLayer attribute) (waveletml.helpers.wavelet_layers.WaveletProductLayer attribute) (waveletml.helpers.wavelet_layers.WaveletSummationLayer attribute) (waveletml.helpers.wavelet_layers.WaveletWeightedLinearLayer attribute) score() (waveletml.models.base_model.BaseModel method) (waveletml.models.gd_wnn.GdWnnClassifier method), [1] (waveletml.models.gd_wnn.GdWnnRegressor method), [1] (waveletml.models.mha_wnn.MhaWnnClassifier method), [1] (waveletml.models.mha_wnn.MhaWnnRegressor method), [1] scores() (waveletml.models.gd_wnn.GdWnnClassifier method), [1] (waveletml.models.gd_wnn.GdWnnRegressor method), [1] seed (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) set_train_test() (waveletml.helpers.data_preparer.Data method) set_weights() (waveletml.models.custom_wnn.BaseCustomWNN method) SinhArcSinhScaler (class in waveletml.helpers.data_scaler)

size_hidden (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) size_input (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) (waveletml.models.mha_wnn.MhaWnnClassifier attribute) (waveletml.models.mha_wnn.MhaWnnRegressor attribute) size_output (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) (waveletml.models.mha_wnn.MhaWnnClassifier attribute) (waveletml.models.mha_wnn.MhaWnnRegressor attribute) split_train_test() (waveletml.helpers.data_preparer.Data method) SqrtScaler (class in waveletml.helpers.data_scaler) SUPPORT (waveletml.helpers.data_preparer.Data attribute) SUPPORTED_ACTIVATIONS (waveletml.models.custom_wnn.BaseCustomWNN attribute) SUPPORTED_CLS_OBJECTIVES (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) SUPPORTED_OPTIMIZERS (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) SUPPORTED_REG_OBJECTIVES (waveletml.models.mha_wnn.BaseMhaWnnModel attribute) SUPPORTED_SCALERS (waveletml.helpers.data_preparer.DataTransformer attribute) SUPPORTED_WAVELETS (waveletml.models.custom_wnn.BaseCustomWNN attribute)

T

task (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) (waveletml.models.mha_wnn.MhaWnnClassifier attribute) (waveletml.models.mha_wnn.MhaWnnRegressor attribute) TimeSeriesDifferencer (class in waveletml.helpers.data_preparer) training (waveletml.helpers.wavelet_layers.WaveletExpansionLayer attribute) (waveletml.helpers.wavelet_layers.WaveletProductLayer attribute) (waveletml.helpers.wavelet_layers.WaveletSummationLayer attribute) (waveletml.helpers.wavelet_layers.WaveletWeightedLinearLayer attribute) (waveletml.models.custom_wnn.BaseCustomWNN attribute) (waveletml.models.custom_wnn.CustomWaveletExpansionNetwork attribute) (waveletml.models.custom_wnn.CustomWaveletProductNetwork attribute) (waveletml.models.custom_wnn.CustomWaveletSummationNetwork attribute) (waveletml.models.custom_wnn.CustomWaveletWeightedLinearNetwork attribute)

transform() (waveletml.helpers.data_preparer.DataTransformer method) (waveletml.helpers.data_scaler.BoxCoxScaler method) (waveletml.helpers.data_scaler.LabelEncoder method) (waveletml.helpers.data_scaler.Log1pScaler method) (waveletml.helpers.data_scaler.LogeScaler method) (waveletml.helpers.data_scaler.ObjectiveScaler method) (waveletml.helpers.data_scaler.OneHotEncoder method) (waveletml.helpers.data_scaler.SinhArcSinhScaler method) (waveletml.helpers.data_scaler.SqrtScaler method) (waveletml.helpers.data_scaler.YeoJohnsonScaler method)

V

valid_mode (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) valid_rate (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute)

verbose (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute)

W

wavelet_fn (waveletml.helpers.wavelet_layers.WaveletExpansionLayer attribute) (waveletml.helpers.wavelet_layers.WaveletProductLayer attribute) (waveletml.helpers.wavelet_layers.WaveletSummationLayer attribute) (waveletml.helpers.wavelet_layers.WaveletWeightedLinearLayer attribute) (waveletml.models.gd_wnn.BaseGdWnnModel attribute) (waveletml.models.gd_wnn.GdWnnClassifier attribute) (waveletml.models.gd_wnn.GdWnnRegressor attribute) wavelet_layer (waveletml.models.custom_wnn.CustomWaveletExpansionNetwork attribute) (waveletml.models.custom_wnn.CustomWaveletProductNetwork attribute) (waveletml.models.custom_wnn.CustomWaveletSummationNetwork attribute) (waveletml.models.custom_wnn.CustomWaveletWeightedLinearNetwork attribute) WaveletExpansionLayer (class in waveletml.helpers.wavelet_layers) waveletml.helpers.callbacks module waveletml.helpers.data_preparer module waveletml.helpers.data_scaler module waveletml.helpers.evaluator module

waveletml.helpers.verifier module waveletml.helpers.wavelet_funcs module waveletml.helpers.wavelet_layers module waveletml.models.base_model module waveletml.models.custom_wnn module waveletml.models.gd_wnn module waveletml.models.mha_wnn module WaveletProductLayer (class in waveletml.helpers.wavelet_layers) WaveletSummationLayer (class in waveletml.helpers.wavelet_layers) WaveletWeightedLinearLayer (class in waveletml.helpers.wavelet_layers) weights (waveletml.helpers.wavelet_layers.WaveletWeightedLinearLayer attribute) wnn_model (waveletml.models.gd_wnn.BaseGdWnnModel attribute)

Y

YeoJohnsonScaler (class in waveletml.helpers.data_scaler)