GSC2.2 Classification

1
GSC2.2 Classification

• GSC II Annual Meeting
• October 2001

2
Single Plate Classification

• Decision tree classifier
• Use ranks to handle plate to plate variation
• 5000 objects in training set
• OC1 oblique decision tree (Murthy et al)
• Build several decision trees let them vote
• Classification categories star / nonstar / defect

3
GSC2.2 Classification

• Unlike astrometry and photometry, where one best
  value was selected per object (per bandpass),
• GSC2.2 classification can combine multiplate
  information to improve the final classifications,
• And counter some known weaknesses.

4
MultiPlate Voting

• For each object
• Collect all single-plate measurements
• Even from plates not being exported, eg IV-N
• Override defect-gtnonstar if N(obs)gt1
• Matched objects likely to be real objects
• Eliminate 25um scan data, if 15um data exist
• Classifier poorly tuned for these scans
• Majority vote of remaining measurements
• Voting classifiers is known to improve results
• Break ties in favor of nonstars
• Compensates for known bias

5
Auxiliary Information the Source Status Flag

• GSC2.2 provides a wealth of additional
  information about each object via the source
  status flag.
• Much of this information is pertinent to the
  quality of the final classification.
• Informed users can further optimize their results
  (eg, guide star selection) with this auxiliary
  data.

6
Status Flag Details 0987654321

• 10 digit decimal mask with relevant info
• Columns 0 blend status
• 9 incomplete processing
• 8 classification voters
• 7 classification unanimity
• 654 photometric details (V,J,F)
• 3 centroider details
• 21 number of plate observations
• 
  

7
Classification and the Status Flag

• 0 blend status
• Poorly tuned for blends gt lower confidence
• 9 incomplete processing
• No features computed gt lower confidence
• 8 classification voters
• Multiple voters gt higher confidence
• 25um voters gt lower confidence

8
Classification and the Status Flag

• 7 classification unanimity
• Unanimous vote gt higher confidence
• 654 photometric details (V,F,J)
• 3 centroider details
• 21 number of plate observations
• More voters gt higher confidence
• 
  

9
Bright Objects

• Tycho stars are included in the GSC2.2.
• Classification was set to star for these objects
• Status flag 9999999900 for Tycho stars
• GSC1 data were omitted from the GSC2.2
• Classifications were excluded from voting
• GSC1 classifier superior for mlt14
• Include GSC1 classification in next export

10
Evaluating Performance Not a simple problem

• What to measure?
• Correctness completeness contamination
• Magnitude and latitude variations
• What to compare against?
• GSCII was constructed because there is nothing
  comparable to it!
• Nonstar ltgt galaxy
• Automatically classified samples are less
  reliable
• Visually classified samples are few and small

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NPM/SPM Starsvs magnitude latitude
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NPM/SPM Galaxiesvs magnitude latitude
13
SDSS Stars and Galaxiesvs magnitude
14
Accuracy vs the real questions

• How complete is my sample of nonstars?
• How pure is my sample of stars?
• What is the probability that the GSC2.2
  classification of this object is correct?
• The answers depend on your sample, as well as on
  the properties of the catalog.
• A single quoted accuracy does not suffice.

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Accuracy vs the real questions

• P(TsS) P(STs)P(Ts) / P(S)
• This formulation is
• Responsive to magnitude and latitude variations
• Adaptable to a priori effects of sampling
• Adaptable to your favorite galaxy model
• Computable (we think! - in progress)
• Answers the real questions.