Data augmentation for machine learning redshifts applied to Sloan Digital Sky Survey galaxies

Monthly Notices of the Royal Astronomical Society

Volumn 450, Issue 1, 2015, Pages 305-316

  Hoyle, Ben ^a,b   Rau, Markus Michael ^a,c   Bonnett, Christopher ^d   Seitz, Stella ^a,c   Weller, Jochen ^a,b,c  

^a UNIVERSITY OF MUNICH   (Germany)

^b EXCELLENCE CLUSTER UNIVERSE   (Germany)

^c MAX PLANCK INSTITUT FÜR EXTRATERRESTRISCHE PHYSIK   (Germany)

^d UNIVERSITAT AUTÒNOMA DE BARCELONA   (Spain)

Author keywords

Catalogues; Galaxies: distances and redshifts; Surveys

Indexed keywords

ARTIFICIAL INTELLIGENCE; E-LEARNING; ERRORS; LEARNING SYSTEMS; PHOTOMETRY; PROBES; RECOVERY; SURVEYS; TREES (MATHEMATICS);

CATALOG; DATA AUGMENTATION; DATA RELEASE; GALAXIES DISTANCES AND REDSHIFTS; PHOTOMETRICS; RED SHIFT; SLOAN DIGITAL SKY SURVEY; TEST SAMPLES; TRAINING SAMPLE; TRAINING SETS;

SAMPLING;

EID: 84929783368     PISSN: 00358711     EISSN: 13652966     Source Type: Journal    
DOI: 10.1093/mnras/stv599     Document Type: Article

References (45)

1. Abazajian K. N. et al., 2009, ApJS, 182, 543.
2. Ahn C. P. et al., 2014, ApJS, 211, 17.
3. Aihara H. et al., 2011, ApJS, 193, 29.
4. Altman N. S., 1992, Am. Stat., 46, 175.
5. Blanton M. R., Roweis S., 2007, AJ, 133, 734.
6. Bonnett C., 2013, preprint (arXiv:e-prints).
7. Breiman L., Friedman J. H., Olshen R. A., Stone C. J., 1984, Classification and Regression Trees. Wadsworth International Group, Belmont, CA.
8. Brimioulle F., Seitz S., Lerchster M., Bender R., Snigula J., 2013, MNRAS, 432, 1046.
9. Bruzual G., Charlot S., 2003, MNRAS, 344, 1000.
10. Budavári T., Szalay A. S., Connolly A. J., Csabai I., Dickinson M., 2000, AJ, 120, 1588.
11. Carrasco Kind M., Brunner R. J., 2013, MNRAS, 432, 1483.
12. Cohen J. G., Hogg D. W., Blandford R., Cowie L. L., Hu E., Songaila A., Shopbell P., Richberg K., 2000, ApJ, 538, 29.
13. Cristiani S. et al., 2000, A & A, 359, 489.
14. Csabai I., Dobos L., Trencséni M., Herczegh G., Józsa P., Purger N., Budavári T., Szalay A. S., 2007, Astron. Nachr., 328, 852.
15. Cunha C. E., Lima M., Oyaizu H., Frieman J., Lin H., 2009, MNRAS, 396, 2379.
16. Dahlen T. et al., 2013, ApJ, 775, 93.
17. Dietterich T. G., 2000, Machine Learning, 40, 139.
18. Drucker H., 1997, in Fisher D. H., ed., Proceedings of the Fourteenth International Conference on Machine Learning, ICML '97. Morgan Kaufmann Publishers Inc., San Francisco, p. 107.
19. Eisenstein D. J. et al., 2011, AJ, 142, 72.
20. Fioc M., Rocca-Volmerange B., 1997, A & A, 326, 950.
21. Freund Y., Schapire R. E., 1997, J. Comput. Syst. Sci., 55, 119.
22. Gerdes D.W., Sypniewski A. J., McKay T. A., Hao J., Weis M. R., Wechsler R. H., Busha M. T., 2010, ApJ, 715, 823.
23. Greisel N., Seitz S., Drory N., Bender R., Saglia R. P., Snigula J., 2013, ApJ, 768, 117.
24. Gunn J. E. et al., 2006, AJ, 131, 2332.
25. Hastie T., Tibshirani R., Friedman J., 2001, The Elements of Statistical Learning: Data Mining, Inference and Prediction. Springer-Verlag, New York.
26. Henriques B. M. B., White S. D. M., Lemson G., Thomas P. A., Guo Q., Marleau G.-D., Overzier R. A., 2012, MNRAS, 421, 2904.
27. Henriques B., White S., Thomas P., Angulo R., Guo Q., Lemson G., Springel V., Overzier R., 2014, preprint (arXiv:e-prints).
28. Hildebrandt H. et al., 2010, A & A, 523, A31.
29. Hoyle B., Rau M. M., Zitlau R., Seitz S., Weller J., 2015, MNRAS, 449, 1275.
30. Kewley L. J., Dopita M. A., Sutherland R. S., Heisler C. A., Trevena J., 2001, ApJ, 556, 121.
31. Lahav O., 1997, in Di Gesu V., Duff M. J. B., Heck A., Maccarone M. C., Scarsi L., Zimmerman H. U., eds, Data Analysis in Astronomy. World Scientific Press, Singapore, p. 43.
32. Lima M., Cunha C. E., Oyaizu H., Frieman J., Lin H., Sheldon E. S., 2008, MNRAS, 390, 118.
33. Maraston C., 2005, MNRAS, 362, 799.
34. Pedregosa F. et al., 2011, J. Machine Learning Res., 12, 2825.
35. Rau M., Seitz S., Brimioulle F., Frank E., Friedrich O., Gruen D., Hoyle B., 2015, preprint (arXiv:1503.08215).
36. Sánchez C. et al., 2014, MNRAS, 445, 1482.
37. Smith J. A. et al., 2002, AJ, 123, 2121.
38. Springel V. et al., 2005, Nature, 435, 629.
39. Tagliaferri R., Longo G., Andreon S., Capozziello S., Donalek C., Giordano G., 2003, in Apolloni B., MarinaroM., Tagliaferri R., eds, Lecture Notes in Computer Science, Vol. 2859, Neural Nets. Springer-Verlag, Berlin, p. 226.
40. The Dark Energy Survey Collaboration 2005, preprint (astro-ph/e-prints)
41. Tojeiro R., Percival W. J., Heavens A. F., Jimenez R., 2011, MNRAS, 413, 434.
42. Vanzella E. et al., 2004, A & A, 423, 761.
43. Wolf C., 2009, MNRAS, 397, 520.
44. Yeche C. et al., 2009, preprint (arXiv:e-prints).
45. York D. G. et al., 2000, AJ, 120, 1579.