Improved Selection Criteria for HII Regions, based on IRAS Sources
  We present new criteria for selecting HII regions from the Infrared
Astronomical Satellite (IRAS) Point Source catalogue (PSC), based on an HII
region catalogue derived manually from the all-sky Wide-field Infrared Survey
Explorer (WISE). The criteria are used to augment the number of HII region
candidates in the Milky Way. The criteria are defined by the linear decision
boundary of two samples: IRAS point sources associated with known HII regions,
which serve as the HII region sample, and IRAS point sources at high Galactic
latitudes, which serve as the non-HII region sample. A machine learning
classifier, specifically a support vector machine (SVM), is used to determine
the decision boundary. We investigate all combinations of four IRAS bands and
suggest that the optimal criterion is log(F$_{\rm 60}$/F$_{\rm
12}$)$\ge$(-0.19$\times$log(F$_{\rm 100}$/F$_{\rm 25}$)+ 1.52), with detections
at 60 and 100 micron. This selects 3041 HII region candidates from the IRAS
PSC. We find that IRAS HII region candidates show evidence of evolution on the
two-colour diagram. Merging the WISE HII catalogue with IRAS HII region
candidates, we estimate a lower limit of approximately 10200 for the number of
HII regions in the Milky Way.
