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Table D.1

Cluster-to-class decision tree.

Cluster Class
0, 3, 6, 11,
14, 20, 21, 30, 33, 38, 39, 40, 42, 47 S
1, 34 D
2 B
5, 25, 26 C
7, 15, 18, 28, 32, 45 V
9, 12, 27, 49 A
16, 48 Q
36 Z
4 P23(z3, z4)/P40(z3, z4) L, S
8, 43 GMM(z2, z4) D, S
10 GMM(z1, z2) R, S
13 GMM(z2, z4) C, O, Q
17, 22, 35,
37, 46 PE(pV)/PM(pV)/Pp(pV) E, M, P, X
19 GMM(z1, z4) C, P
23 GMM(z1, z4) L, M
24 GMM(z2, z3) K, M
A, B, C,
29 GMM(z1, z2) D, M, P,
S, Q, V
31 GMM(z3, z4) K, L
37 GMM(z2, z4) L, M
41 GMM(z1, z2) B, V
44 PE(pV)/PM(pV) E, S
Class is B, C, P, or X and h-feature is present Ch

Notes. Overview of the computation of the asteroid-class probability for each observation based on its cluster probabilities. The upper part of the table contains clusters whose members are mapped to a single asteroid class. The lower part contains clusters where the resulting asteroid class probabilities depend on the criterion given in the middle column. GMM(zx, zy) means that the cluster probability is split based on a Gaussian mixture model with N components fit to all cluster members in zx and zy, where N is equal to the number of possible outcome classes (i.e. each mixture component represents one candidate class). PX(y) refers to the probability of belonging to the class or cluster X given the value of y. The last line gives the definition of the Ch-class, which is the last step of the classification.

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