Publication
Fusing Vantage Point Trees and Linear Discriminants for Fast Feature Classification
| dc.contributor.author | Proença, H. | |
| dc.contributor.author | Neves, João | |
| dc.date.accessioned | 2020-02-10T14:21:54Z | |
| dc.date.available | 2020-02-10T14:21:54Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | This paper describes a classification strategy that can be regarded as amore general form of nearest-neighbor classification. It fuses the concepts ofnearestneighbor,linear discriminantandVantage-Pointtrees, yielding an efficient indexingdata structure and classification algorithm. In the learning phase, we define a set ofdisjoint subspaces of reduced complexity that can be separated by linear discrimi-nants, ending up with an ensemble of simple (weak) classifiers that work locally. Inclassification, the closest centroids to the query determine the set of classifiers con-sidered, which responses are weighted. The algorithm was experimentally validatedin datasets widely used in the field, attaining error rates that are favorably compara-ble to the state-of-the-art classification techniques. Lastly, the proposed solution hasa set of interesting properties for a broad range of applications: 1) it is determinis-tic; 2) it classifies in time approximately logarithmic with respect to the size of thelearning set, being far more efficient than nearest neighbor classification in terms ofcomputational cost; and 3) it keeps the generalization ability of simple models. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1007/s00357-017-9223-0 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.6/9173 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Image classification | pt_PT |
| dc.subject | Vantage-point tree | pt_PT |
| dc.subject | Linear discriminants | pt_PT |
| dc.subject | Nearest neighbor classification | pt_PT |
| dc.title | Fusing Vantage Point Trees and Linear Discriminants for Fast Feature Classification | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| person.familyName | Proença | |
| person.givenName | Hugo | |
| person.identifier | 1153590 | |
| person.identifier.ciencia-id | ED16-81E7-0319 | |
| person.identifier.orcid | 0000-0003-2551-8570 | |
| person.identifier.rid | F-9499-2010 | |
| person.identifier.scopus-author-id | 14016540600 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 16ca2fc4-5379-43a6-8867-ba63bd9289e0 | |
| relation.isAuthorOfPublication.latestForDiscovery | 16ca2fc4-5379-43a6-8867-ba63bd9289e0 |