Fig. A.2

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Illustration of recursive feature elimination. The top panel illustrates the evolution of the average precision of our classifier with the number of features. The bottom panel illustrates the evolution of the importance of individual features, as the least important feature is recursively removed. The shaded bar indicates the set of features we found to be optimal.
The curves indicate the parameters numbered by their reverse order of elimination: (1) SigCombined, (2) ModSigCurv, (3) LP_beta, (4) LP_SigCurv, (5) K24, (6) SymLat, (7) Frac_Variability, (8) EFluxErr, (9) HR34, (10) Variability_Index, (11) HR45, (12) PL_Index, (13) HR 12, (14) DeltaInd, (15) SymLon, (16) K13, (17) Pivot_Energy, (18) LP_Index, (19) K35, (20) HR23.
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