Monotonic classification: An overview on algorithms, performance measures and data sets
Currently, knowledge discovery in databases is an essential first step when identifying valid,
novel and useful patterns for decision making. There are many real-world scenarios, such as …
novel and useful patterns for decision making. There are many real-world scenarios, such as …
The state-of-art of the generalizations of the Choquet integral: From aggregation and pre-aggregation to ordered directionally monotone functions
In 2013, Barrenechea et al. used the Choquet integral as an aggregation function in the
fuzzy reasoning method (FRM) of fuzzy rule-based classification systems. After that, starting …
fuzzy reasoning method (FRM) of fuzzy rule-based classification systems. After that, starting …
Multiple criteria sorting models and methods—Part I: survey of the literature
Multiple criteria sorting methods assign objects into ordered categories while objects are
characterized by a vector of n attributes values. Categories are ordered, and the assignment …
characterized by a vector of n attributes values. Categories are ordered, and the assignment …
Fuzzy ensemble of deep learning models using choquet fuzzy integral, coalition game and information theory for breast cancer histology classification
Millions of women, worldwide, suffer from breast cancer and a large number of them
succumb to death. In recent years, computer-aided diagnosis (CAD) systems are being …
succumb to death. In recent years, computer-aided diagnosis (CAD) systems are being …
Robust ordinal regression in preference learning and ranking
Abstract Multiple Criteria Decision Aiding (MCDA) offers a diversity of approaches designed
for providing the decision maker (DM) with a recommendation concerning a set of …
for providing the decision maker (DM) with a recommendation concerning a set of …
Deep preference learning for multiple criteria decision analysis
K Martyn, M Kadziński - European Journal of Operational Research, 2023 - Elsevier
We propose preference learning algorithms for inferring the parameters of a threshold-
based sorting model from large sets of assignment examples. The introduced framework is …
based sorting model from large sets of assignment examples. The introduced framework is …
[图书][B] Discrete fuzzy measures
This book is about computational aspects of fuzzy measures—nonadditive measures
defined on discrete sets X. Our main focus is on multicriteria decision making and the …
defined on discrete sets X. Our main focus is on multicriteria decision making and the …
Choquet integral and coalition game-based ensemble of deep learning models for COVID-19 screening from chest X-ray images
Under the present circumstances, when we are still under the threat of different strains of
coronavirus, and since the most widely used method for COVID-19 detection, RT-PCR is a …
coronavirus, and since the most widely used method for COVID-19 detection, RT-PCR is a …
Integrating machine learning models to learn potentially non-monotonic preferences for multi-criteria sorting from large-scale assignment examples
Learning preferences from assignment examples has attracted considerable attention in the
field of multi-criteria sorting (MCS). However, traditional MCS methods, designed to infer …
field of multi-criteria sorting (MCS). However, traditional MCS methods, designed to infer …
[HTML][HTML] Incremental elicitation of Choquet capacities for multicriteria choice, ranking and sorting problems
This paper proposes incremental preference elicitation methods for multicriteria decision
making with a Choquet integral. The Choquet integral is an evaluation function that performs …
making with a Choquet integral. The Choquet integral is an evaluation function that performs …