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lecture07-090330
- Vapnik-Cheervonenkis (VC) Dimension Support Vector Machines SVM Applications Committee machines PAC Learning Boosting “No Free Lunch” Theorem-Vapnik-Cheervonenkis (VC) Dimension
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，并简单叙述了机器学习的相关算法，包括决策树算法、随机森林算
Machine-Learning-Materials
- 北航计算机学院研究生机器学习课程讲义，涵盖了机器学习领域大部分内容，如SVM、EM、boosting等。深入浅出，易于自学-Beihang University Graduate School of Computer Science Machine Learning Lecture Notes, covering most of machine learning, such as SVM, EM, boosting and so on. Easy to understand and self-l
A-New-Boosting-Multi-class-SVM-Algorithm
- This article discuss a new algorithm for boosting Multi_class support vector machine and demonstrate the experimental result based on developing this algorithm.
fdtool
- 利用局部二位模式和haar特征进行人脸或目标识别。-This toolbox provides some tools for objects/faces detection using Local Binary Patterns (and some variants) and Haar features. Object/face detection is performed by evaluating trained models over multi-scan windows with
pkupr
- 模式识别 北京大学 本科生课程 课件 （包括贝叶斯模型、最近邻、SVM、线性与非线性分类器、boosting、统计学习、非监督学习等）-Pattern Recognition Peking University Courseware (including Bayesian model, the nearest neighbor, SVM, linear and non-linear classifiers, boosting, statistical learning, unsupervised
boosting_demo
- boosting算法用于集成学习，包含多种弱分类器(Boosting algorithm is used for ensemble learning, and it contains many weak classifiers)