arXiv Open Access 2012

A Bayesian Boosting Model

Alexander Lorbert David M. Blei Robert E. Schapire Peter J. Ramadge

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Abstrak

We offer a novel view of AdaBoost in a statistical setting. We propose a Bayesian model for binary classification in which label noise is modeled hierarchically. Using variational inference to optimize a dynamic evidence lower bound, we derive a new boosting-like algorithm called VIBoost. We show its close connections to AdaBoost and give experimental results from four datasets.

Topik & Kata Kunci

stat.ML

Penulis (4)

Alexander Lorbert

David M. Blei

Robert E. Schapire

Peter J. Ramadge

Format Sitasi

APA MLA BibTeX

Lorbert, A., Blei, D.M., Schapire, R.E., Ramadge, P.J. (2012). A Bayesian Boosting Model. https://arxiv.org/abs/1209.1996

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2012
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓