.. vim: set fileencoding=utf-8 : .. Andre Anjos .. Mon 25 Nov 09:43:43 2013 CET .. .. Copyright (C) 2011-2013 Idiap Research Institute, Martigny, Switzerland .. _bob.learn.boosting: =========================================================================================== Generalized Boosting Framework using Stump and Look Up Table (LUT) based Weak Classifiers =========================================================================================== .. todolist:: The package implements a generalized boosting framework, which incorporates different boosting approaches. The implementation is a mix of pure Python code and C++ implementations of identified bottle-necks, including their python bindings. The Boosting algorithms implemented in this package are: 1) Gradient Boost [Fri00]_ (generalized version of Adaboost [FS99]_) for univariate cases using stump decision classifiers, as in [VJ04]_. 2) TaylorBoost [SMV11]_ for univariate and multivariate cases using Look-Up-Table based classifiers [Ata12]_ .. [Fri00] *Jerome H. Friedman*. **Greedy function approximation: a gradient boosting machine**. Annals of Statistics, 29:1189--1232, 2000. .. [FS99] *Yoav Freund and Robert E. Schapire*. **A short introduction to boosting**. Journal of Japanese Society for Artificial Intelligence, 14(5):771-780, September, 1999. .. [VJ04] *Paul Viola and Michael J. Jones*. **Robust real-time face detection**. International Journal of Computer Vision (IJCV), 57(2): 137--154, 2004. .. [SMV11] *Mohammad J. Saberian, Hamed Masnadi-Shirazi, Nuno Vasconcelos*. **TaylorBoost: First and second-order boosting algorithms with explicit margin control**. IEEE Conference on Conference on Computer Vision and Pattern Recognition (CVPR), 2929--2934, 2011. .. [Ata12] *Cosmin Atanasoaei*. **Multivariate boosting with look-up tables for face processing**. PhD Thesis, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, 2012. Documentation ------------- .. toctree:: :maxdepth: 2 guide example py_api Indices and tables ------------------ * :ref:`genindex` * :ref:`modindex` * :ref:`search`