We present a search for Standard Model Higgs Boson production in
association with a W boson using 2.7 fb-1 of CDF data. We
select events with a high-pT lepton, a neutrino, and two
jets. At least one of the jets must be identified as a b-quark jet
(tagged). We optimized two multivariate discriminants designed to
separate signal from background. One discriminant uses complementary
Matrix Element and Boosted Decision Tree techniques. The other uses
Neural Networks. We perform binned likelihood fits of the
discriminants and set 95% confidence level upper limits on the WH
production cross section times branching ratio as a function of
Higgs mass for each analysis technique. In order to improve
sensitivity, the multivariate outputs of both analyses are then
combined into a super-discriminant by using a neural network. This
combination results in about a 15% improvement over the previous
blessed results from either individual analysis.
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