These methods try to preserve the generalization ability of SVM by choosing a specific number of effective samples and features [8]. They assist in inordinate ...
Sep 11, 2020 · Training support vector machines (SVMs) for pixel-based feature extraction purposes from aerial images requires selecting representative ...
Nov 23, 2020 · The results reveal that DR.LSH outperforms them in terms of both preservation rate and maintaining the generalization ability (classification ...
DR.LSH can significantly reduce the number of instances and execution time. Training support vector machines (SVMs) for pixel-based feature extraction purposes ...
We present a newly developed IS method called Valid Border Recognition (VBR). VBR selects the closest heterogeneous neighbors as valid border instances.
DR.LSH is a fast instance selection method. Training classifiers, especially Support Vector Machines (SVM) on huge datasets is usually slow due to their high ...
Sep 1, 2023 · Aslani M., Seipel S., A fast instance selection method for support vector machines in building extraction, Applied Soft Computing 97 (2020).
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Based on clustering technique, Chen et al. [12] proposed an instance selection algorithm for speeding up support vector machines. ...
A simple and reliable instance selection for fast training support vector machine: Valid Border Recognition.
This paper presents an instance selection method especially for multi-class problems. With cluster centers of positive class as reference points instances are ...
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