hgboost is to minimize the function for xgboost, catboost or lightboost over a hyper-parameter space by using cross-validation, and evaluating the results on an independent validation set. hgboost can be applied for classification and regression tasks.
bnlearn is for learning the graphical structure of Bayesian networks in Python.
HNet stands for graphical Hypergeometric NEtworks, which is a method where associations across variables are tested for significance by statistical inference.
distfit is for probability density function fitting of univariate distributions of non-censored data.
classeval is to evaluate the models performance for any kind of two-class or multi-class model.
findpeaks is Python package for the detection of peaks and valleys in 1 dimensional vectors and (2D) images.