搜索资源列表
boostingDemo
- BOOSTING DEMO, A VERY USEFUL DEMO FOR ADABOOST
multiboost-0.71.bin.tar
- boosting multiclass,a class library for machine learning
Baggingboostingandc45
- 模式识别bagging boosting c4.5算法-Bagging boosting c4.5 algorithm for pattern recognition
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
Gradient_Feature_Selection_for_Online_Boosting
- 关于on-line boosting的gradient feature selection的介绍-With regard to on-line boosting the introduction of gradient feature selection
code
- 基于boosting的人脸检测的matlab实现-Boosting-based face detection matlab implementation
gentleBoost
- 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
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
adaptive_adaboosting
- 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 met
lecture07-090330
- Vapnik-Cheervonenkis (VC) Dimension Support Vector Machines SVM Applications Committee machines PAC Learning Boosting “No Free Lunch” Theorem-Vapnik
The_Status_Quo_of_Machine_Learning_of_Artificial_I
- 机器学习是人工智能的一个子领域，是人工智能中非常活跃且范围甚广的主要核心研究领域之一，也是现代智能系统的关键环节和瓶颈。机器学习吸取了人工智能、概率统计、计算复杂性理论、控制论、信息论、哲学、生理学、神经生物学等学科的成果，主要关注于开发一些让计算机可以自动学习的技术，并通过经验提高系统自身的性能。本文介绍了机器学习的概念、基本结构和发展，以及各种机器学习方法，包括机械学习、归纳学习、类比学习、解释学习、基于神经网络的学习以及知识发现等
Rapid_Object_Detection
- A very fast and robust object detection fr a mework. A very simple set of Haar like box features A commensurating Image representation (that enables fast calculation of features, feature scaling and normalizati
Boosting
- adaboost算法原理，详细分析，并附有例子介绍-adaboost, gentel
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
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 examp
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
boostingtree
- 关于boosting tree 的新算法-boosting tree
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