Name
Abstract | ||
|---|---|---|
Classification involves associating instances with particular classes by maximizing intra-class similarities and minimizing inter-class simi larities. Thus, the way similarity among instances is measured is crucial for the success of the system. In case-based reasoning, it is assumed that similar problems have similar solutions. The case-based approach to classification is founded on retrieving cases from the case base that are similar to a given problem, and associating the problem with the class containing the most similar cases. Similarity-based retrieval tools can advantageously be us ed in building flexible retrieval and classification systems. Case-based classific ation uses previously classified instances to label unknown instances with proper classes. Classification accuracy is affected by the retrieval process - the more relevant the ins tances used for classification, the greater the accuracy. The paper presents a novel approach to case-based classification. The algorithm is based on a notion of similarity assessment and was developed for supporting flexible retrieval of relevant information. Case similarity is asse ssed with respect to a given context that defines constraints for matching. Context relaxation and restriction is used for controlling the classification accuracy. The validity of the proposed approach is tested on real-world domains, and the system's performance , in terms of accuracy and scalability, is compared to that of other machine learning a lgorithms. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1142/S0218213097000268 | International Journal on Artificial Intelligence Tools |
Keywords | Field | DocType |
context-based similarity,classification,case-based reasoning,rele- vance assessment.,case base reasoning,machine learning,classification system,case based reasoning | Data mining,One-class classification,Pattern recognition,Context based,Computer science,Case base,Artificial intelligence,Case-based reasoning,Machine learning,Scalability,Multiclass classification | Journal |
Volume | Issue | Citations |
6 | 4 | 13 |
PageRank | References | Authors |
1.08 | 21 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Igor Jurisica | 1 | 616 | 45.55 |
| Janice I. Glasgow | 2 | 392 | 127.97 |