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Bitfusion co-founder and CEO Subbu Rama and COO Maciej Bajkowski tell me that a lot of its early users were especially excited about using Boost for machine learning and data science projects.
RAPSearch2 was implemented in C++ using Boost library 1.42 (http://www.boost.org/) and threadpool 0.2.5 (http://threadpool.sourceforge.net/), and was tested extensively on Linux platforms.
The computational portions of the MetaPhase method consist of software written in C++ using Boost (http://www.boost.org) with auxiliary scripts written in Perl and bash.
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We would like to minimise this quantity using boosting techniques.
This section describes such a scheme using boosting techniques.
Section 6 discusses an algorithm, introduced in [3], for word error rate minimisation using boosting techniques.
The algorithm is applied to ensemble-based learning by using boosting to construct cascades of classifiers.
Using boosting techniques at the utterance level was thought to lead to a method for reducing the word error rate.
Using boosted regression trees we disentangled the role of anthropogenic factors, physiography, weather and vegetation on fire activity.
The spatial distributions of six fishes with contrasting biogeographies were modeled using boosted regression trees and multiscale landscape data.
Propensity scores were estimated using boosted CART 24 since logistic regression did not achieve good balance.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com