feyn.tools

Common helper functions that makes it easier to get started using the SDK.

function split

def split(
    data: Iterable,
    ratio: List[float] = [1, 1],
    random_state: int = None
) -> List[Iterable]

Split datasets into random subsets

This function is used to split a dataset into random subsets - typically training and test data.

The input dataset should be either a pandas DataFrames or a dictionary of numpy arrays. The ratio parameter controls how the data is split, and how many subsets it is split into.

Example: Split data in the ratio 2:1 into train and test data
>>> train, test = feyn.tools.split(data, [2,1])

Example: Split data in to train, test and validation data. 80% training data and 10% validation and holdout data each
>>> train, validation, holdout = feyn.tools.split(data, [.8, .1, .1])

Arguments:
    data -- The data to split (DataFrame or dict of numpy arrays).
    ratio -- the size ratio of the resulting subsets
    random_state -- the random state of the split (integer)

Returns:
    list of subsets -- Subsets of the dataset (same type as the input dataset).

function sympify_model

def sympify_model(
    m,
    signif=6,
    symbolic_lr=False,
    include_weights=True
)