| Full text | |
| Author(s): |
Jodas, Danilo Samuel
;
Passos, Leandro Aparecido
;
Adeel, Ahsan
;
Papa, Joao Paulo
;
IEEE
Total Authors: 5
|
| Document type: | Journal article |
| Source: | 2022 29TH INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING (IWSSIP); v. N/A, p. 4-pg., 2022-01-01. |
| Abstract | |
Demands for minimum parameter setup in machine learning models are desirable to avoid time-consuming optimization processes. The k-Nearest Neighbors is one of the most effective and straightforward models employed in numerous problems. Despite its well-known performance, it requires the value of k for specific data distribution, thus demanding expensive computational efforts. This paper proposes a k-Nearest Neighbors classifier that bypasses the need to define the value of k. The model computes the k value adaptively considering the data distribution of the training set. We compared the proposed model against the standard k-Nearest Neighbors classifier and two parameterless versions from the literature. Experiments over 11 public datasets confirm the robustness of the proposed approach, for the obtained results were similar or even better than its counterpart versions. (AU) | |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 19/07665-4 - Center for Artificial Intelligence |
| Grantee: | Fabio Gagliardi Cozman |
| Support Opportunities: | Research Grants - Research Program in eScience and Data Science - Research Centers in Engineering Program |
| FAPESP's process: | 17/02286-0 - Probabilistic models for commercial losses detection |
| Grantee: | André Nunes de Souza |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 19/18287-0 - Real-time Urban Forest Management Using Machine Learning |
| Grantee: | Danilo Samuel Jodas |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 18/21934-5 - Network statistics: theory, methods, and applications |
| Grantee: | André Fujita |
| Support Opportunities: | Research Projects - Thematic Grants |