TY - JOUR
T1 - Vector piece-wise regression versus clustering (definition and comparative analysis)
AU - Brailovsky, Victor L.
PY - 1992/4
Y1 - 1992/4
N2 - The problem of vector piece-wise regression is formulated. The case where the domain of definition of a vector response function consists of a number of regions of smoothness is considered. The number of the regions and their boundaries are not known and they should be found by analysing a sample of signal corrupted by noise. The solution may be obtained by combination of a dynamic programming algorithm and a probabilistic estimate. The comparison with the approach based on cluster analysis technique, is considered and some experimental results are presented.
AB - The problem of vector piece-wise regression is formulated. The case where the domain of definition of a vector response function consists of a number of regions of smoothness is considered. The number of the regions and their boundaries are not known and they should be found by analysing a sample of signal corrupted by noise. The solution may be obtained by combination of a dynamic programming algorithm and a probabilistic estimate. The comparison with the approach based on cluster analysis technique, is considered and some experimental results are presented.
KW - Vector piece-wise regression
KW - cluster analysis
KW - dynamic programming
KW - probabilistic estimate
UR - http://www.scopus.com/inward/record.url?scp=44049123792&partnerID=8YFLogxK
U2 - 10.1016/0167-8655(92)90073-9
DO - 10.1016/0167-8655(92)90073-9
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AN - SCOPUS:44049123792
SN - 0167-8655
VL - 13
SP - 227
EP - 235
JO - Pattern Recognition Letters
JF - Pattern Recognition Letters
IS - 4
ER -