Computer Recognition Systems 4 pp 119-125 | Cite as
Prototype Extraction of a Single-Class Area for the Condensed 1-NN Rule
Conference paper
Abstract
The paper presents a new condensation algorithm based on the idea of a sample representativeness. For each sample in a dataset a representative measure is counted. Starting with samples with the highest value of the measure, each sample and all its voters (which constitute single-class area) are condensed in one averaged prototype-sample. The algorithm is tested on nine well-known datasets and compared with Jozwik’s condensation methods.
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