International Journal of Approximate Reasoning最新文献

Adding imprecision to hypotheses: A Bayesian framework for testing practical significance in nonparametric settings

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-28 DOI: 10.1016/j.ijar.2024.109332

Rodrigo F.L. Lassance , Rafael Izbicki , Rafael B. Stern

{"title":"Adding imprecision to hypotheses: A Bayesian framework for testing practical significance in nonparametric settings","authors":"Rodrigo F.L. Lassance , Rafael Izbicki , Rafael B. Stern","doi":"10.1016/j.ijar.2024.109332","DOIUrl":"10.1016/j.ijar.2024.109332","url":null,"abstract":"<div><div>Instead of testing solely a precise hypothesis, it is often useful to enlarge it with alternatives deemed to differ negligibly from it. For instance, in a bioequivalence study one might test if the concentration of an ingredient is exactly the same in two drugs. In such a context, it might be more relevant to test the enlarged hypothesis that the difference in concentration between them is of no practical significance. While this concept is not alien to Bayesian statistics, applications remain mostly confined to parametric settings and strategies that effectively harness experts' intuitions are often scarce or nonexistent. To resolve both issues, we introduce the Pragmatic Region Oriented Test (<span>PROTEST</span>), an accessible nonparametric testing framework based on distortion models that can seamlessly integrate with Markov Chain Monte Carlo (MCMC) methods and is available as an <span>R</span> package. We develop expanded versions of model adherence, goodness-of-fit, quantile and two-sample tests. To demonstrate how <span>PROTEST</span> operates, we use examples, simulated studies that critically evaluate features of the test and an application on neuron spikes. Furthermore, we address the crucial issue of selecting the threshold—which controls how much a hypothesis is to be expanded—even when intuitions are limited or challenging to quantify.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109332"},"PeriodicalIF":3.2,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cautious classifier ensembles for set-valued decision-making 用于集值决策的谨慎分类器组合

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-26 DOI: 10.1016/j.ijar.2024.109328

Haifei Zhang , Benjamin Quost , Marie-Hélène Masson

{"title":"Cautious classifier ensembles for set-valued decision-making","authors":"Haifei Zhang , Benjamin Quost , Marie-Hélène Masson","doi":"10.1016/j.ijar.2024.109328","DOIUrl":"10.1016/j.ijar.2024.109328","url":null,"abstract":"<div><div>Classifiers now demonstrate impressive performances in many domains. However, in some applications where the cost of an erroneous decision is high, set-valued predictions may be preferable to classical crisp decisions, being less informative but more reliable. Cautious classifiers aim at producing such imprecise predictions so as to reduce the risk of making wrong decisions. In this paper, we describe two cautious classification approaches rooted in the ensemble learning paradigm, which consist in combining probability intervals. These intervals are aggregated within the framework of belief functions, using two proposed strategies that can be regarded as generalizations of classical averaging and voting. Our strategies aim at maximizing the lower expected discounted utility to achieve a good compromise between model accuracy and determinacy. The efficiency and performance of the proposed procedure are illustrated using imprecise decision trees, thus giving birth to cautious variants of the random forest classifier. The performance and properties of these variants are illustrated using 15 datasets.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"177 ","pages":"Article 109328"},"PeriodicalIF":3.2,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Existence of optimal strategies in bimatrix game and applications 双矩阵博弈中最优策略的存在及其应用

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-22 DOI: 10.1016/j.ijar.2024.109329

Sana Afreen, Ajay Kumar Bhurjee

{"title":"Existence of optimal strategies in bimatrix game and applications","authors":"Sana Afreen, Ajay Kumar Bhurjee","doi":"10.1016/j.ijar.2024.109329","DOIUrl":"10.1016/j.ijar.2024.109329","url":null,"abstract":"<div><div>This paper delves into interval-valued bimatrix games, where precise payoffs remain elusive, but lower and upper bounds on payoffs can be determined. The study explores several key questions in this context. Firstly, it addresses the issue of the existence of a universally applicable equilibrium across all instances of interval values. The paper establishes a fundamental equivalence by demonstrating that this property hinges on the solvability of a specific system of interval linear inequalities. Secondly, the research endeavors to characterize the comprehensive set of weak and strong equilibrium using a system of interval linear inequalities. The findings in this paper shed light on the complexities and intricacies of interval-valued bimatrix games, offering valuable insights into their equilibrium properties and computational aspects. Through illustrative examples, we underscore the practical utility of these approaches and compare them with previously developed state-of-the-art methods, demonstrating their ability to generate conservative solutions in the face of interval uncertainty. The findings of this research not only offer valuable insights into the equilibrium properties and computational aspects of interval-valued bimatrix games but extend their practical implications. In particular, the paper delves into real-life applications, exemplifying the significance of these findings for crude oil trading decision-making.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"177 ","pages":"Article 109329"},"PeriodicalIF":3.2,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An approach to calculate conceptual distance across multi-granularity based on three-way partial order structure 基于三向偏序结构的多粒度概念距离计算方法

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-22 DOI: 10.1016/j.ijar.2024.109327

Enliang Yan , Pengfei Zhang , Tianyong Hao , Tao Zhang , Jianping Yu , Yuncheng Jiang , Yuan Yang

{"title":"An approach to calculate conceptual distance across multi-granularity based on three-way partial order structure","authors":"Enliang Yan , Pengfei Zhang , Tianyong Hao , Tao Zhang , Jianping Yu , Yuncheng Jiang , Yuan Yang","doi":"10.1016/j.ijar.2024.109327","DOIUrl":"10.1016/j.ijar.2024.109327","url":null,"abstract":"<div><div>The computation of concept distances aids in understanding the interrelations among entities within knowledge graphs and uncovering implicit information. The existing studies predominantly focus on the conceptual distance of specific hierarchical levels without offering a unified framework for comprehensive exploration. To overcome the limitations of unidimensional approaches, this paper proposes a method for calculating concept distances at multiple granularities based on a three-way partial order structure. Specifically: (1) this study introduces a methodology for calculating inter-object similarity based on the three-way attribute partial order structure (APOS); (2) It proposes the application of the similarity matrix to delineate the structure of categories; (3) Based on the similarity matrix describing the three-way APOS of categories, we establish a novel method for calculating inter-category distance. The experiments on eight datasets demonstrate that this approach effectively differentiates various concepts and computes their distances. When applied to classification tasks, it exhibits outstanding performance.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"177 ","pages":"Article 109327"},"PeriodicalIF":3.2,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust Bayesian causal estimation for causal inference in medical diagnosis 用于医学诊断因果推理的稳健贝叶斯因果估计

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-22 DOI: 10.1016/j.ijar.2024.109330

Tathagata Basu , Matthias C.M. Troffaes

{"title":"Robust Bayesian causal estimation for causal inference in medical diagnosis","authors":"Tathagata Basu , Matthias C.M. Troffaes","doi":"10.1016/j.ijar.2024.109330","DOIUrl":"10.1016/j.ijar.2024.109330","url":null,"abstract":"<div><div>Causal effect estimation is a critical task in statistical learning that aims to find the causal effect on subjects by identifying causal links between a number of predictor (or, explanatory) variables and the outcome of a treatment. In a regressional framework, we assign a treatment and outcome model to estimate the average causal effect. Additionally, for high dimensional regression problems, variable selection methods are also used to find a subset of predictor variables that maximises the predictive performance of the underlying model for better estimation of the causal effect. In this paper, we propose a different approach. We focus on the variable selection aspects of high dimensional causal estimation problem. We suggest a cautious Bayesian group LASSO (least absolute shrinkage and selection operator) framework for variable selection using prior sensitivity analysis. We argue that in some cases, abstaining from selecting (or, rejecting) a predictor is beneficial and we should gather more information to obtain a more decisive result. We also show that for problems with very limited information, expert elicited variable selection can give us a more stable causal effect estimation as it avoids overfitting. Lastly, we carry a comparative study with synthetic dataset and show the applicability of our method in real-life situations.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"177 ","pages":"Article 109330"},"PeriodicalIF":3.2,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Incremental attribute reduction with α,β-level intuitionistic fuzzy sets 用 α、β 级直观模糊集递减属性

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-14 DOI: 10.1016/j.ijar.2024.109326

Pham Viet Anh , Nguyen Ngoc Thuy , Le Hoang Son , Tran Hung Cuong , Nguyen Long Giang

{"title":"Incremental attribute reduction with α,β-level intuitionistic fuzzy sets","authors":"Pham Viet Anh , Nguyen Ngoc Thuy , Le Hoang Son , Tran Hung Cuong , Nguyen Long Giang","doi":"10.1016/j.ijar.2024.109326","DOIUrl":"10.1016/j.ijar.2024.109326","url":null,"abstract":"<div><div>The intuitionistic fuzzy set theory is recognized as an effective approach for attribute reduction in decision information systems containing numerical or continuous data, particularly in cases of noisy data. However, this approach involves complex computations due to the participation of both the membership and non-membership functions, making it less feasible for data tables with a large number of objects. Additionally, in some practical scenarios, dynamic data tables may change in the number of objects, such as the addition or removal of objects. To overcome these challenges, we propose a novel and efficient incremental attribute reduction method based on <span><math><mi>α</mi><mo>,</mo><mi>β</mi></math></span>-level intuitionistic fuzzy sets. Specifically, we first utilize the key properties of <span><math><mi>α</mi><mo>,</mo><mi>β</mi></math></span>-level intuitionistic fuzzy sets to construct a distance measure between two <span><math><mi>α</mi><mo>,</mo><mi>β</mi></math></span>-level intuitionistic fuzzy partitions. This extension of the intuitionistic fuzzy set model helps reduce noise in the data and shrink the computational space. Subsequently, we define a new reduct and design an efficient algorithm to identify an attribute subset in fixed decision tables. For dynamic decision tables, we develop two incremental calculation formulas based on the distance measure between two <span><math><mi>α</mi><mo>,</mo><mi>β</mi></math></span>-level intuitionistic fuzzy partitions to improve processing time. Accordingly, some important properties of the distance measures are also clarified. Finally, we design two incremental attribute reduction algorithms that handle the addition and removal of objects. Experimental results have demonstrated that our method is more effective than incremental methods based on fuzzy rough set and intuitionistic fuzzy set approaches in terms of execution time and classification accuracy from the obtained reduct.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"176 ","pages":"Article 109326"},"PeriodicalIF":3.2,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142654677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fuzzy centrality measures in social network analysis: Theory and application in a university department collaboration network 社会网络分析中的模糊中心度量：大学院系协作网络中的理论与应用

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-13 DOI: 10.1016/j.ijar.2024.109319

Annamaria Porreca , Fabrizio Maturo , Viviana Ventre

{"title":"Fuzzy centrality measures in social network analysis: Theory and application in a university department collaboration network","authors":"Annamaria Porreca , Fabrizio Maturo , Viviana Ventre","doi":"10.1016/j.ijar.2024.109319","DOIUrl":"10.1016/j.ijar.2024.109319","url":null,"abstract":"<div><div>The motivation behind this research stems from the inherent complexity and vagueness in human social interactions, which traditional Social Network Analysis (SNA) approaches often fail to capture adequately. Conventional SNA methods typically represent relationships as binary or weighted ties, thereby losing the subtle nuances and inherent uncertainty in real-world social connections. The need to preserve the vagueness of social relations and provide a more accurate representation of these relationships motivates the introduction of a fuzzy-based approach to SNA. This paper proposes a novel framework for Fuzzy Social Network Analysis (FSNA), which extends traditional SNA to accommodate the vagueness of relationships. The proposed method redefines the ties between nodes as fuzzy numbers rather than crisp values and introduces a comprehensive set of fuzzy centrality indices, including fuzzy degree centrality, fuzzy betweenness centrality, and fuzzy closeness centrality, among others. These indices are designed to measure the importance and influence of nodes within a network while preserving the uncertainty in the relationships between them. The applicability of the proposed framework is demonstrated through a case study involving a university department's collaboration network, where relationships between faculty members are analyzed using data collected via a fascinating mouse-tracking technique.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"176 ","pages":"Article 109319"},"PeriodicalIF":3.2,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142654678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Goal-hiding information-seeking dialogues: A formal framework 目标隐藏的信息搜索对话：正式框架

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-13 DOI: 10.1016/j.ijar.2024.109325

Andreas Brännström, Virginia Dignum, Juan Carlos Nieves

{"title":"Goal-hiding information-seeking dialogues: A formal framework","authors":"Andreas Brännström, Virginia Dignum, Juan Carlos Nieves","doi":"10.1016/j.ijar.2024.109325","DOIUrl":"10.1016/j.ijar.2024.109325","url":null,"abstract":"<div><div>We consider a type of information-seeking dialogue between a seeker agent and a respondent agent, where the seeker estimates the respondent to not be willing to share a particular set of sought-after information. Hence, the seeker postpones (hides) its goal topic, related to the respondent's sensitive information, until the respondent is perceived as willing to talk about it. In the intermediate process, the seeker opens other topics to steer the dialogue tactfully towards the goal. Such dialogue strategies, which we refer to as goal-hiding strategies, are common in diverse contexts such as criminal interrogations and medical assessments, involving sensitive topics. Conversely, in malicious online interactions like social media extortion, similar strategies might aim to manipulate individuals into revealing information or agreeing to unfavorable terms. This paper proposes a formal dialogue framework for understanding goal-hiding strategies. The dialogue framework uses Quantitative Bipolar Argumentation Frameworks (QBAFs) to assign willingness scores to topics. An initial willingness for each topic is modified by considering how topics promote (support) or demote (attack) other topics. We introduce a method to identify relations among topics by considering a respondent's shared information. Finally, we introduce a gradual semantics to estimate changes in willingness as new topics are opened. Our formal analysis and empirical evaluation show the system's compliance with privacy-preserving safety properties. A formal understanding of goal-hiding strategies opens up a range of practical applications; For instance, a seeker agent may plan with goal-hiding to enhance privacy in human-agent interactions. Similarly, an observer agent (third-party) may be designed to enhance social media security by detecting goal-hiding strategies employed by users' interlocutors.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"177 ","pages":"Article 109325"},"PeriodicalIF":3.2,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Anomaly detection based on improved k-nearest neighbor rough sets 基于改进的 k 近邻粗糙集的异常检测

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-13 DOI: 10.1016/j.ijar.2024.109323

Xiwen Chen , Zhong Yuan , Shan Feng

{"title":"Anomaly detection based on improved k-nearest neighbor rough sets","authors":"Xiwen Chen , Zhong Yuan , Shan Feng","doi":"10.1016/j.ijar.2024.109323","DOIUrl":"10.1016/j.ijar.2024.109323","url":null,"abstract":"<div><div>Neighborhood rough set model is a resultful model for processing incomplete, imprecise, and other uncertain data. It has been used in several fields, such as anomaly detection and data classification. However, most of the current neighborhood rough set models suffer from the issues of unreasonable neighborhood radius determination and poor adaptability. To obtain an adaptive neighborhood radius and make granulation results more reasonable, an improved <em>k</em>-nearest neighbor rough set model is proposed in the paper by introducing <em>k</em>th-distance as the <em>k</em>-nearest neighborhood radius, and an anomaly detection model is constructed. In the method, the <em>k</em>-nearest neighborhood radius is used to calculate the <em>k</em>-nearest neighbor relation firstly. Then, the anomaly degree of granule (GAD) is defined to measure the anomaly degree of <em>k</em>-nearest neighbor granules by combining approximation accuracy with the local density. Furthermore, the GADs of an object's <em>k</em>-nearest neighbor granules generated by different attribute subsets are calculated, and the anomaly score (AS) is constructed. Finally, an anomaly detection algorithm is designed. Some mainstream anomaly detection methods are compared with the proposed method on public datasets. The results indicate that the capability of detecting anomalies of the proposed approach outperforms current detection methods.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"176 ","pages":"Article 109323"},"PeriodicalIF":3.2,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142654676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Inner product reduction for fuzzy formal contexts 模糊形式语境的内积还原

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2024-11-08 DOI: 10.1016/j.ijar.2024.109324

Qing Wang , Xiuwei Gao

引用次数: 0