A method for exploiting domain information in astrophysical parameter estimation
| dc.creator | Bailer-Jones, C. A. L. | |
| dc.date | 2007-11-28 | |
| dc.date.accessioned | 2026-07-07T08:45:49Z | |
| dc.date.available | 2026-07-07T08:45:49Z | |
| dc.description | I outline a method for estimating astrophysical parameters (APs) from multidimensional data. It is a supervised method based on matching observed data (e.g. a spectrum) to a grid of pre-labelled templates. However, unlike standard machine learning methods such as ANNs, SVMs or k-nn, this algorithm explicitly uses domain information to better weight each data dimension in the estimation. Specifically, it uses the sensitivity of each measured variable to each AP to perform a local, iterative interpolation of the grid. It avoids both the non-uniqueness problem of global regression as well as the grid resolution limitation of nearest neighbours. | |
| dc.description | Proceedings of ADASS17 (September 2007, London). 4 pages. To appear in ASP Conf. Proc | |
| dc.identifier | https://arxiv.org/abs/0711.4465 | |
| dc.identifier | http://arxiv.org/abs/0711.4465 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/143082 | |
| dc.subject | Astrophysics | |
| dc.title | A method for exploiting domain information in astrophysical parameter estimation | |
| dc.type | text |