Framework for the Item Response Theory analysis of dichotomous and ordinal polytomous outcomes under the assumption of within-item multidimensionality and discreteness of the latent traits. The fitting algorithms allow for missing responses and for different item parametrizations and are based on the Expectation-Maximization paradigm. Individual covariates affecting the class weights may be included in the new version together with possibility of constraints on all model parameters.

Conjoint measurement is a psychophysical procedure in which stimulus pairs are presented that vary along 2 or more dimensions and the observer is required to compare the stimuli along one of them.  This package contains functions to estimate the contribution of the n scales to the judgment by a maximum likelihood method under several hypotheses of how the perceptual dimensions interact. Reference: Knoblauch & Maloney (2012) "Modeling Psychophysical Data in R". <doi:10.1007/978-1-4614-4475-6>.

Provides several classifiers based on probabilistic models. These classifiers allow to model the dependence structure of continuous features through bivariate copula functions and graphical models, see Salinas-Gutiérrez et al. (2014) <doi:10.1007/s00180-013-0457-y>.

Contains a collection of datasets for working with machine learning tasks.
    It will contain datasets for supervised machine learning Jiang (2020)<doi:10.1016/j.beth.2020.05.002> and will include datasets for classification and regression.
    The aim of this package is to use data generated around health and other domains.

Exploratory data analysis and manipulation functions for multi-
    label data sets along with an interactive Shiny application to ease their use.

Large collection of multilabel datasets along with the functions
    needed to export them to several formats, to make partitions, and to obtain
    bibliographic information.

Collection of the state of the art multi-label resampling algorithms. The objective of these algorithms is to achieve balance in multi-label datasets.