X = {x1,...xN} ∈ RN×D
|
Eq. (1) |
The target data set with N data instances and D dimensions |
XT = {x1,T,...xNT,T} ∈ RNT ×
D
|
Eqs. (5) and (12)
|
The data set in the target domain with NT data instances and D dimensions |
U = [μij]C×N
|
Eq. (1) |
The C × N membership matrix with μij indicating the membership degree of xj(j = 1,..., N) belonging to cluster i(i = 1,…, C) |
UT = [μij,T]CT×NT
|
Eqs. (5) and (12)
|
The generated CT ×NT membership matrix in the target domain with μij,T indicating the membership degree of xj(j = 1,..., NT) belonging to cluster i (i = 1,…, CT) |
PT&S = [pjk]CT×CS
|
Eq. (5) |
The matching degree matrix with pjk indicating the matching degree of the jth estimated cluster prototype in the target domain to the kth cluster prototype in the source domain; CT and CS denote the cluster numbers in the target and source domains respectively |
V = [v1,···,vC]T
|
Eq. (1) |
The cluster prototype matrix with vi = [vi1, ···, viD]T (i = 1,..., C) signifying the ith cluster prototype (centroid) |
VT = [v1,T, ···,
vCT,T]T
|
Eqs. (4),(5),(11), and (12)
|
The cluster prototype matrix in the target domain with vj,T = [vj1,T, ···, vjD,T]T (j = 1,..., CT) signifying the jth cluster prototype (centroid) |
|
Generated in the knowledge matching stage, and used in the knowledge utilization stage |
The raw cluster prototypes in the target domain estimated by KL-PM with
signifying the jth raw cluster prototype (centroid) |
VS = [v1,S, ···,
vCS,S]T
|
Eqs. (4),(5), and (11)
|
The cluster prototype matrix in the source domain with vk,S = [vk1,S, ···, vkD,S]T (k = 1,..., CS) signifying the kth cluster prototype (centroid) |
ṼS = [ṽ1,S, ···,
ṽCT,S]T
|
Eqs. (9)–(12); Generated in the knowledge matching stage, and used in the knowledge utilization stage |
The employed cluster representatives from the source domain for the eventual knowledge utilization in the target domain with ṽ
j,S = [ṽj1,S, ···, ṽjD,S]T (j = 1,..., CT) denoting the jth cluster representative in the source domain |