The paper presents a review of the basic concepts of the Logical Analysis of Data (LAD),
along with a series of discrete optimization models associated to the implementation of …

Disaggregation methods have become popular in multicriteria decision aiding (MCDA) for
eliciting preferential information and constructing decision models from decision examples …

Logical analysis of data (LAD), an approach to data analysis based on Boolean functions,
combinatorics, and optimization, can be considered one of the methods of interpretable …

This paper applies the Logical Analysis of Data (LAD) to detect and diagnose faults in
industrial chemical processes. This machine learning classification technique discovers …

It is practical that industrial processes are regarded as hybrid systems involving both
continuous and discrete variables. Particularly, process discrete variables are usually rather …

Pattern generation methods for the Logical Analysis of Data (LAD) have been term-
enumerative in nature. In this paper, we present a Mixed 0–1 Integer and Linear …

Most of the reported prognostic techniques use a small number of condition indicators
and/or use a thresholding strategies in order to predict the remaining useful life (RUL). In this …

This paper presents the implementation of a novel multi-class diagnostic technique for the
detection and identification of faults based on an approach called logical analysis of data …

Abstract Logical Analysis of Data (LAD) is a data analysis methodology introduced by Peter
L. Hammer in 1986. LAD distinguishes itself from other classification and machine learning …

Given a binary dataset of positive and negative observations, a positive (negative) pattern is
a subcube having a nonempty intersection with the positive (negative) subset of the dataset …