BaseModel

class tfts.models.base.BaseModel(predict_sequence_length: int = 1, config: BaseConfig | None = None)

Bases: ABC

Bert model for time series forecasting.

This model implements a transformer-based architecture (BERT) adapted for time series data. It processes time series inputs through a transformer encoder and produces predictions for future time steps.

Parameters:

• predict_sequence_length (int, optional) – Number of future time steps to predict, by default 1

• config (BertConfig, optional) – Configuration parameters for the model, by default None

Inherited-members:

Methods

build_model(inputs)
compute_output_shape(input_shape)
get_config()
load_pretrained_weights(weights_dir)
predict(x, **kwargs)
save_model(weights_dir)
save_pretrained(save_directory[, ...])
save_weights(weights_path)
summary()
to_model()