搜索结果

Statistical-Learning-Theory The goal of statistical learning theory is to study, in a statistical framework, the properties of learning algorithms. In particular, most results take the form of so-called error bounds. This tutorial introduces the techniques that are used to obtain such results.

Support Vector Machine is small sample method based on statistic learning theory. It is a new method to deal with the highly nonlinear classification and regression problems .It can better deal with the small sample, nonlinear and

机器学习经典书籍The Elements of Statistical Learning--Data Mining, Inference and Prediction. 作者：Friedman

最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, ...

模式识别学习综述.该论文的英文参考文献为303篇.很有可读价值.Abstract— Classical and recent results in statistical pattern recognition and learning theory are reviewed in a two-class pattern classification setting. This basic model best illustrates intuition and analysis techniques while still contain ...

Learning Kernel Classifiers: Theory and Algorithms, Introduction This chapter introduces the general problem of machine learning and how it relates to statistical inference. 1.1 The Learning Problem and (Statistical) Inference It was only a few years after the introduction of the first computer that ...

YASMET: Yet Another Small MaxEnt Toolkit (Statistical Machine Learning) 由Franz Josef Och编写，一个简短但非常经典的最大熵统计模型实现源码。

Machine Learning, Neural and Statistical Classification Editors: D. Michie, D.J. Spiegelhalter, C.C. Taylor February 17, 1994

Information theory, inference and learning algorithms 

Bayes networks. From theory to application. E book document for advanced bayes theory and statistical model