Classification and regression trees, as well as their variants, are off-the-shelf methods in
Machine Learning. In this paper, we review recent contributions within the Continuous …

Automatic legal text classification systems have been proposed in the literature to address
knowledge extraction from judgments and detect their aspects. However, most of these …

Welfare measures overall utility across a population, whereas malfare measures overall
disutility, and the social planner's problem can be cast either as maximizing the former or …

We propose a tree‐based algorithm (μCART) for classification and regression problems in
the context of functional data analysis, which allows to leverage measure learning and …

Concerns about the effect of greenhouse gases have motivated the development of
certification protocols to quantify the industrial carbon footprint (cf). These protocols are …

A new splitting criterion for classification trees that generates better decision rules in terms of
interpretability is proposed in this paper. The criterion is designed to find homogeneous …

Most real-world datasets have a heterogeneous feature space composed of binary,
categorical, ordinal, and continuous features. However, the currently available local …

Even though warehouses are becoming increasingly automated, humans remain their
central and most important resource. Every day, various activities must be carried out by …

The field of machine learning is subject to an increasing interest in models that are not only
accurate but also interpretable and robust, thus allowing their end users to understand and …

Interpreting and explaining complex models such as ensemble machine learning models for
opinion mining is essential to increase the level of transparency fairness and reliability of …