Common helper functions that makes it easier to get started using the SDK.
def split( data: Iterable, ratio: List[float] = [1, 1] ) -> 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 Returns: list of subsets -- Subsets of the dataset (same type as the input dataset).
def sympify_graph( g, signif=6, symbolic_lr=False )