TY - JOUR
T1 - Substantial improvements in the set-covering projection classifier CHIRP (composite hypercubes on iterated random projections)
AU - Wilkinson, Leland
AU - Anand, Anushka
AU - Dang, Tuan Nhon
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2012/12
Y1 - 2012/12
N2 - In Wilkinson et al. [2011] we introduced a new set-covering random projection classifier that achieved average error lower than that of other classifiers in the Weka platform. This classifier was based on an L∞ norm distance function and exploited an iterative sequence of three stages (projecting, binning, and covering) to deal with the curse of dimensionality, computational complexity, and nonlinear separability. We now present substantial changes that improve robustness and reduce training and testing time by almost an order of magnitude without jeopardizing CHIRP's outstanding error performance.
AB - In Wilkinson et al. [2011] we introduced a new set-covering random projection classifier that achieved average error lower than that of other classifiers in the Weka platform. This classifier was based on an L∞ norm distance function and exploited an iterative sequence of three stages (projecting, binning, and covering) to deal with the curse of dimensionality, computational complexity, and nonlinear separability. We now present substantial changes that improve robustness and reduce training and testing time by almost an order of magnitude without jeopardizing CHIRP's outstanding error performance.
KW - Random projections
KW - Supervised classification
UR - http://www.scopus.com/inward/record.url?scp=84878562629&partnerID=8YFLogxK
U2 - 10.1145/2382577.2382583
DO - 10.1145/2382577.2382583
M3 - Article
AN - SCOPUS:84878562629
VL - 6
JO - ACM Transactions on Knowledge Discovery from Data
JF - ACM Transactions on Knowledge Discovery from Data
SN - 1556-4681
IS - 4
M1 - 19
ER -