[HTML][HTML] Mathematical optimization in classification and regression trees
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 …
Machine Learning. In this paper, we review recent contributions within the Continuous …
[HTML][HTML] Automatic explanation of the classification of Spanish legal judgments in jurisdiction-dependent law categories with tree estimators
J González-González, F de Arriba-Pérez… - Journal of King Saud …, 2023 - Elsevier
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 …
knowledge extraction from judgments and detect their aspects. However, most of these …
Uncertainty and the social planner's problem: Why sample complexity matters
C Cousins - Proceedings of the 2022 ACM Conference on Fairness …, 2022 - dl.acm.org
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 …
disutility, and the social planner's problem can be cast either as maximizing the former or …
Measure inducing classification and regression trees for functional data
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 …
the context of functional data analysis, which allows to leverage measure learning and …
Explainable automatic industrial carbon footprint estimation from bank transaction classification using natural language processing
J González-González, S García-Méndez… - IEEE …, 2022 - ieeexplore.ieee.org
Concerns about the effect of greenhouse gases have motivated the development of
certification protocols to quantify the industrial carbon footprint (cf). These protocols are …
certification protocols to quantify the industrial carbon footprint (cf). These protocols are …
A new splitting criterion for better interpretable trees
S Hwang, HG Yeo, JS Hong - IEEE Access, 2020 - ieeexplore.ieee.org
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 …
interpretability is proposed in this paper. The criterion is designed to find homogeneous …
ORANGE: Opposite-label soRting for tANGent Explanations in heterogeneous spaces
Most real-world datasets have a heterogeneous feature space composed of binary,
categorical, ordinal, and continuous features. However, the currently available local …
categorical, ordinal, and continuous features. However, the currently available local …
Optimizing workforce allocation under uncertain activity duration
Even though warehouses are becoming increasingly automated, humans remain their
central and most important resource. Every day, various activities must be carried out by …
central and most important resource. Every day, various activities must be carried out by …
Interpretable Quantile Regression by Optimal Decision Trees
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 …
accurate but also interpretable and robust, thus allowing their end users to understand and …
Opinion Mining with Interpretable Random Density Forests
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 …
opinion mining is essential to increase the level of transparency fairness and reliability of …