Improved selection criteria for H ii regions, based on IRAS sources.

We present new criteria for selecting H  ii regions from the Infrared Astronomical Satellite (IRAS) Point Source Catalogue (PSC), based on an H  ii region catalogue derived manually from the all-sky Wide-field Infrared Survey Explorer (WISE). The criteria are used to augment the number of H  ii region candidates in the Milky Way. The criteria are defined by the linear decision boundary of two samples: IRAS point sources associated with known H  ii regions, which serve as the H  ii region sample, and IRAS point sources at high Galactic latitudes, which serve as the non-H  ii region sample. A machine learning classifier, specifically a support vector machine, is used to determine the decision boundary. We investigate all combinations of four IRAS bands and suggest that the optimal criterion is |$\mathrm{log}\left(F_{60}/F_{12}\right)\geqq \left(-0.19 \times \mathrm{log}\left(F_{100}/F_{25}\right)+ 1.52\right)$|⁠, with detections at 60 and 100  |${\mu}$| m. This selects 3041 H  ii region candidates from the IRAS PSC. We find that IRAS H  ii region candidates show evidence of evolution on the two-colour diagram. Merging the WISE H  ii catalogue with IRAS H  ii region candidates, we estimate a lower limit of approximately 10 200 for the number of H  ii regions in the Milky Way. [ABSTRACT FROM AUTHOR]