scholarly journals A Compact Evolutionary Interval-Valued Fuzzy Rule-Based Classification System for the Modeling and Prediction of Real-World Financial Applications With Imbalanced Data

2015 ◽  
Vol 23 (4) ◽  
pp. 973-990 ◽  
Author(s):  
Jose Antonio Sanz ◽  
Dario Bernardo ◽  
Francisco Herrera ◽  
Humberto Bustince ◽  
Hani Hagras
Keyword(s):  
Real World ◽  
Classification System ◽  
Imbalanced Data ◽  
Fuzzy Rule ◽  
Rule Based ◽  
Financial Applications ◽  
Modeling And Prediction ◽  
Interval Valued

scholarly journals Medical diagnosis of cardiovascular diseases using an interval-valued fuzzy rule-based classification system

2014 ◽  
Vol 20 ◽  
pp. 103-111 ◽  
Author(s):  
José Antonio Sanz ◽  
Mikel Galar ◽  
Aranzazu Jurio ◽  
Antonio Brugos ◽  
Miguel Pagola ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Classification System ◽  
Medical Diagnosis ◽  
Fuzzy Rule ◽  
Rule Based ◽  
Interval Valued

Deep Fuzzy Rule-based Classification System with Improved Wang-Mendel Method

2021 ◽  
pp. 1-1
Author(s):  
Yuangang Wang ◽  
Haoran Liu ◽  
Wenjuan Jia ◽  
Shuo Guan ◽  
Xiaodong Liu ◽  
...  
Keyword(s):  
Classification System ◽  
Fuzzy Rule ◽  
Rule Based

A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets

2008 ◽  
Vol 159 (18) ◽  
pp. 2378-2398 ◽  
Author(s):  
Alberto Fernández ◽  
Salvador García ◽  
María José del Jesus ◽  
Francisco Herrera
Keyword(s):  
Imbalanced Data ◽  
Fuzzy Rule ◽  
Classification Systems ◽  
Data Sets ◽  
Rule Based ◽  
Imbalanced Data Sets

Modified Fuzzy Rule-Based Classification System for Early Warning of Student Learning

2019 ◽  
Vol 48 (3) ◽  
pp. 385-406 ◽  
Author(s):  
Qun Zhao ◽  
Jin-Long Wang ◽  
Tsang-Long Pao ◽  
Li-Yu Wang
Keyword(s):  
Student Learning ◽  
Classification System ◽  
Prediction Accuracy ◽  
Confusion Matrix ◽  
Great Influence ◽  
Fuzzy Rule ◽  
Two Dimensions ◽  
Learning Performance ◽  
Rule Based

This study uses the log data from Moodle learning management system for predicting student learning performance in the first third of a semester. Since the quality of the data has great influence on the accuracy of machine learning, five major data transmission methods are used to enhance data quality of log file in the data preprocessing stage. Furthermore, the modified FRBCS-CHI (fuzzy rule-based classification system using Chi's technique) algorithm, based on the weighted consequence, is proposed to improve the prediction accuracy of classification. Thereafter, the confusion matrix with two dimensions is employed to illustrate the prediction results, such as false positives, false negatives, true positives, and true negatives, which are further used to produce the parameters of prediction performance, including the precision rate, the recall rate, and the F-measure. From the results of experiment, the proposed modified FRBCS-CHI method will have higher prediction accuracy than the original FRBCS-CHI method.

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