Case-based classification using similarity-based retrieval

Classification involves associating instances with particular classes by maximizing intra-class similarities and minimizing inter-class similarities. 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. Validity of the proposed approach is tested on real world domains, and the system´s performance is compared to that of other machine learning algorithms.