Symbolic Representation of Neural Networks
Computer - Special issue: neural computing: companion issue to Spring 1996 IEEE Computational Science & Engineering
Comparing case-based reasoning classifiers for predicting high risk software components
Journal of Systems and Software
Feature Weight Maintenance in Case Bases Using Introspective Learning
Journal of Intelligent Information Systems
Case Representation Issues for Case-Based Reasoning from Ensemble Research
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Predicting Fault-Prone Modules with Case-Based Reasoning
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
Toward Global Optimization of Case-Based Reasoning Systems for Financial Forecasting
Applied Intelligence
The Journal of Machine Learning Research
A k-mean clustering algorithm for mixed numeric and categorical data
Data & Knowledge Engineering
A hybrid case adaptation approach for case-based reasoning
Applied Intelligence
Neighborhood rough set based heterogeneous feature subset selection
Information Sciences: an International Journal
Gaussian case-based reasoning for business failure prediction with empirical data in China
Information Sciences: an International Journal
Majority voting combination of multiple case-based reasoning for financial distress prediction
Expert Systems with Applications: An International Journal
Breast mass classification based on cytological patterns using RBFNN and SVM
Expert Systems with Applications: An International Journal
Improved use of continuous attributes in C4.5
Journal of Artificial Intelligence Research
Improved heterogeneous distance functions
Journal of Artificial Intelligence Research
Case-based reasoning and fuzzy logic in fault diagnosis
WSEAS Transactions on Computers
Expert Systems with Applications: An International Journal
A case-based classifier for hypertension detection
Knowledge-Based Systems
Introducing attribute risk for retrieval in case-based reasoning
Knowledge-Based Systems
Case-based reasoning support for liver disease diagnosis
Artificial Intelligence in Medicine
Expert Systems with Applications: An International Journal
Two layered Genetic Programming for mixed-attribute data classification
Applied Soft Computing
Using ensembles of binary case-based reasoners
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
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Development of classification methods using case-based reasoning systems is an active area of research. In this paper, two new case-based reasoning systems with two similarity measures that support mixed categorical and numerical data as well as only categorical data are proposed. The principal difference between these two measures lies in the calculations of distance for categorical data. The first one, named distance in unsupervised learning (DUL), is derived from co-occurrence of values, and the other one, named distance in supervised learning (DSL), is used to calculate the distance between two values of the same feature with respect to every other feature for a given class. However, the distance between numerical data is computed using the Euclidean distance. Furthermore, the importance of numeric features is determined by linear discrimination analysis (LDA) and the weight assignment to categorical features depends on co-occurrence of feature values when calculating the similarity between a new case and the old one. The performance of the proposed case-based reasoning systems has been investigated on the University of California, Irvine (UCI) data sets by 5-fold cross validation. The results indicate that these case-based reasoning systems will produce a proper performance in predictive accuracy and interpretability.