Simple Stat Only Model

class simple_stat_only_model.model.Model(get_train_set=None, systematics=None)

Bases: object

fit()

Trains the model.

Params:: None
Functionality:: This function can be used to train a model. If re_train is True, it balances the dataset, fits the model using the balanced dataset, and saves the model. If re_train is False, it loads the saved model and calculates the saved information. The saved information is used to compute the train results.
Returns:: None

predict(test_set)

Predicts the values for the test set.

Parameters:: test_set (dict): A dictionary containing the test data, and weights.
Returns:: dict: A dictionary with the following keys: * ‘mu_hat’: The predicted value of mu. * ‘delta_mu_hat’: The uncertainty in the predicted value of mu. * ‘p16’: The lower bound of the 16th percentile of mu. * ‘p84’: The upper bound of the 84th percentile of mu.

simple_stat_only_model.model.train_test_split(data_set, test_size=0.2, random_state=42, reweight=False)