| DOI | Resolve DOI: https://doi.org/10.1007/978-3-031-73110-5_1 |
|---|
| Author | Search for: Richard, René1ORCID identifier: https://orcid.org/0000-0002-1342-6225; Search for: Belacel, Nabil1ORCID identifier: https://orcid.org/0000-0003-1731-3225 |
|---|
| Affiliation | - National Research Council of Canada. Digital Technologies
|
|---|
| Format | Text, Article |
|---|
| Conference | Future Technologies Conference, FTC 2024, November 14-15, 2024, London, United Kingdom |
|---|
| Abstract | In scenarios where obtaining real-time labels proves challenging, conventional approaches may result in sub-optimal performance. This paper presents an optimal strategy for streaming contexts with limited labeled data, introducing an adaptive technique for unsupervised regression. The proposed method leverages a sparse set of initial labels and introduces an innovative drift detection mechanism to enable dynamic model adaptations in response to evolving patterns in the data. To enhance adaptability, we integrate the ADWIN (ADaptive WINdowing) algorithm with error generalization based on Root Mean Square Error (RMSE). ADWIN facilitates real-time drift detection, while RMSE provides a robust measure of model prediction accuracy. This combination enables our multivariate method to effectively navigate the challenges of streaming data, continuously adapting to changing patterns while maintaining a high level of predictive precision. We evaluate the performance of our multivariate method across various public datasets, comparing it to non-adapting baselines. Through comprehensive assessments, we demonstrate the superior efficacy of our adaptive regression technique for tasks where obtaining labels in real-time is a significant challenge. The results underscore the method’s capacity to outperform traditional approaches and highlight its potential in scenarios characterized by label scarcity and evolving data patterns. |
|---|
| Publication date | 2024-11-05 |
|---|
| Publisher | Springer Nature |
|---|
| In | |
|---|
| Series | |
|---|
| Language | English |
|---|
| Peer reviewed | Yes |
|---|
| Export citation | Export as RIS |
|---|
| Report a correction | Report a correction (opens in a new tab) |
|---|
| Record identifier | 6c38eaa8-c0cb-4eb9-922c-602898ad1160 |
|---|
| Record created | 2024-11-07 |
|---|
| Record modified | 2024-11-14 |
|---|
