搜索资源列表
On-line-Boosting-and-Vision
- 在计算机视觉的应用中，对于检测和识别任务boosting算法是一个很流行的算法。对比于非在线算法，在线的boosting算法可以更好的适应实时跟踪的应用。
adaptive_adaboosting.rar
- AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files ,AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm t
gentleBoost.rar
- 当前流行的机器学习算法之一：boosting的变体——Gentleboost,The current popular one of machine learning algorithms: boosting variants- Gentleboost
boostingtree
- 关于boosting tree 的新算法-boosting tree
Logitboost
- Logitboost 是一种改进的boosting算法，可以用作参考-Logitboost is an improved boosting algorithm can be used as a reference
adaboost_for_matlab
- AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learnin
bagging-and-boosting-NNE
- 主要是给新手熟悉bagging和boosting算法在虹膜中的运用。-bagging and boosting algorithm in the application of the iris.
Baggingboostingandc45
- 模式识别bagging boosting c4.5算法-Bagging boosting c4.5 algorithm for pattern recognition
code
- 基于boosting的人脸检测的matlab实现-Boosting-based face detection matlab implementation
lecture07-090330
- Vapnik-Cheervonenkis (VC) Dimension Support Vector Machines SVM Applications Committee machines PAC Learning Boosting “No Free Lunch” Theorem-Vapnik-Cheervonenkis (VC) Dimension
Rapid_Object_Detection
- A very fast and robust object detection framework. A very simple set of Haar like box features A commensurating Image representation (that enables fast calculation of features, feature scaling and normalization) Efficient feature selectio
boosting-survey
- Boosting is a general method for improving the accuracy of any given learning algorithm. Focusing primarily on the AdaBoost algorithm, this chapter overviews some of the recent work on boosting including analyses of AdaBoost’s training error an
the_application_of_Boosting
- 集成 学 习 算法通过训练多个弱学习算法并将其结论进行合成，可以显著地提 高学习系统的泛化能力。Boosting算法作为集成学习算法的主要代表算法，得到 了广泛的研究和应用，但其研究成果大部分都集中的分类问题上。-Integrated learning algorithm through the training of more than a weak learning algorithm and its conclusions synthesis, can significantly
LocBoost
- Classify using the local boosting algorithm
adaboost
- AdaBoost程序 Boosting是近年来流行的一种用来提高学习算法精度的方法。以 AdaBoost算法为例介绍了 Boosting算法 。-Boosting daBoost program in recent years a popular learning algorithm is used to improve the accuracy of the method. AdaBoost algorithm to an example introduced the Boosting alg
adaboost_version1b
- 最经典AdaBoost实现，适合初学，有大量详细的注释，容易理解-This a classic AdaBoost implementation, in one single file with easy understandable code. The function consist of two parts a simple weak classifier and a boosting part: The weak classifier tries to find the b
boostingdisplay
- boosting的演示文件，matlab7.0，需自己添加数据-boosting the presentations, matlab7.0, add your own data to be
boost_neural_network
- 结合boosting与神经网络方法相结合的分类方法，效果好，识别率高-Combining boosting and neural network approach for robust classification, effective with high recognition rate
2008_bmvc
- Weighted Sampling for Large-Scale Boosting 关于从大量数据中学习的-Weighted Sampling for Large-Scale Boosting on data from a large study
A Short Introduction to Boosting
- 关于分类算法Boosting的介绍。介绍了Boosting的核心思想，以及不可忽视的重要细节问题。(A Short Introduction to Boosting)