hoi.core.get_entropy

hoi.core.get_entropy#

hoi.core.get_entropy(method='gc', **kwargs)[source]#

Get entropy function.

Parameters:

method{‘gc’, ‘gauss’, ‘binning’, ‘histogram’, ‘knn’, ‘kernel’}

Name of the method to compute entropy. Use either :

‘gc’: gaussian copula entropy [default]. See
hoi.core.entropy_gc()

‘gauss’: gaussian entropy. See hoi.core.entropy_gauss()

‘binning’: estimator to use for discrete variables. See
hoi.core.entropy_bin()

‘histogram’estimator based on binning the data, to estimate
the probability distribution of the variables and then compute the differential entropy. For more details see hoi.core.entropy_hist()

‘knn’: k-nearest neighbor estimator. See
hoi.core.entropy_knn()

‘kernel’: kernel-based estimator of entropy
see hoi.core.entropy_kernel()

A custom entropy estimator can be provided. It should be a
callable function written with Jax taking a single 2D input of shape (n_features, n_samples) and returning a float.

kwargsdict | {}