[HTML][HTML] Increasing trust in AI through privacy preservation and model explainability: Federated Learning of Fuzzy Regression Trees
Federated Learning (FL) lets multiple data owners collaborate in training a global model
without any violation of data privacy, which is a crucial requirement for enhancing users' trust …
without any violation of data privacy, which is a crucial requirement for enhancing users' trust …
Reinforced fuzzy rule-based neural networks realized through streamlined feature selection strategy and fuzzy clustering with distance variation
In this article, we present a dimensionality reduction methodology of reinforced fuzzy-rule-
based neural networks (FRNNs) realized with the help of determination/correlation …
based neural networks (FRNNs) realized with the help of determination/correlation …
Federated Learning of XAI Models in Healthcare: A Case Study on Parkinson's Disease
Artificial intelligence (AI) systems are increasingly used in healthcare applications, although
some challenges have not been completely overcome to make them fully trustworthy and …
some challenges have not been completely overcome to make them fully trustworthy and …
Designing distributed fuzzy rule-based models
In the design of fuzzy rule-based models, in the presence of high-dimensional data, we are
faced with conceptual and algorithmic challenges. Conceptually, as the dimensionality of …
faced with conceptual and algorithmic challenges. Conceptually, as the dimensionality of …
Learning compact zero-order TSK fuzzy rule-based systems for high-dimensional problems using an Apriori+ local search approach
Learning fuzzy rule-based systems entails searching a set of fuzzy rules which fits the
training data. Even if using fix fuzzy partitions, the amount of rules that can be formed is …
training data. Even if using fix fuzzy partitions, the amount of rules that can be formed is …
Increasing accuracy and explainability in fuzzy regression trees: An experimental analysis
Regression Trees (RTs) have been widely used in the last decades in various domains, also
thanks to their inherent explainability. Fuzzy RTs (FRTs) extend RTs by using fuzzy sets and …
thanks to their inherent explainability. Fuzzy RTs (FRTs) extend RTs by using fuzzy sets and …
Design of reinforced fuzzy model driven to feature selection through univariable-based correlation and multivariable-based determination coefficient analysis
In this article, we introduce a design methodology of reinforced fuzzy models based both on
univariate analysis and multivariable analysis to cope with high-dimensional problems. This …
univariate analysis and multivariable analysis to cope with high-dimensional problems. This …
Building efficient fuzzy regression trees for large scale and high dimensional problems
Regression trees (RTs) are simple, but powerful models, which have been widely used in
the last decades in different scopes. Fuzzy RTs (FRTs) add fuzziness to RTs with the aim of …
the last decades in different scopes. Fuzzy RTs (FRTs) add fuzziness to RTs with the aim of …
Generation of first-order TSK rules based on the apriori+ search approach
In this work, we propose several algorithms for learning first-order TSK fuzzy rules. These
methods, consist of two stages: first, they generate a set of candidate rules with an …
methods, consist of two stages: first, they generate a set of candidate rules with an …
정보이득 및 퍼지 엔트로피를 이용한 퍼지 클러스터링기반 신경회로망의 차원 축소에 관한 연구
김은후， 오성권 - 한국지능시스템학회 논문지, 2022 - dbpia.co.kr
본 논문에서는 정보이득과 퍼지 엔트로피를 결합한 특징선택 방법을 제안하고, 이를 퍼지
클러스터링기반 신경회로망의 차원축소 기능으로 사용하는 설계 방법론을 제안한다 …
클러스터링기반 신경회로망의 차원축소 기능으로 사용하는 설계 방법론을 제안한다 …