E.G的专栏

PageRank： http://en.wikipedia.org/wiki/Page_rank ; http://download.youkuaiyun.com/source/376367BM25：http://download.youkuaiyun.com/source/376362RankBoost: http://download.youkuaiyun.com/source/376396PRanking: htt

Wiki ref: http://en.wikipedia.org/wiki/MinimaxMinimax (sometimes minmax) is a method in decision theory for minimizing the maximum possible loss. Alternatively, it can be thought of as maximizing th

        One of the central challenges of computer science is to get a computer to do what needs to be done, without telling it how to do it. Genetic programming addresses this challenge by providing a

Wiki ref: http://en.wikipedia.org/wiki/Simulated_annealingSimulated annealing (SA) is a generic probabilistic meta-algorithm for the global optimization problem, namely locating a good approximation

Quoted From Wiki.Vapnik-Chervonenkis DimensionIn computational learning theory, the VC dimension (for Vapnik-Chervonenkis dimension) is a measure of the capacity of a statistical classification al

K-MEANS算法（基本上符合EM算法）：      k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。        k-means 算法的工作过程说明如下：首先从n个数据对象任意选择 k 个对象作为初始聚类中

Wiki Ref： http://en.wikipedia.org/wiki/Support_vector_machine Source Code and Help Docs: http://download.youkuaiyun.com/source/377387SMO Algorithm: http://d.download.youkuaiyun.com/down/377392/xlliu0226SV

K-Nearest Neighbour Algorithm(Wiki ref) http://en.wikipedia.org/wiki/K-nearest_neighbor_algorithmRadial Basis Function(Wiki ref) http://en.wikipedia.org/wiki/Radial_basis_functionInstanced-Based

Wiki: http://en.wikipedia.org/wiki/Naive_bayes   Algorithm From Christopher D. Mannings Information Retrieval  TRAINBERNOULLINB(C,D)1 V ← EXTRACTVOCABULARY(D)2 N ← COUNTDOCS(D)3 for each

把从混合信号中求出主分量（能量最大的成份）的方法称为主分量分析（PCA），而次分量（Minor Components,MCs）与主分量（Principal Components,PCs）相对，它是混合信号中能量最小的成分，被认为是不重要的或是噪声有关的信号，把确定次分量的方法称为次分量分析（MCA）.      PCA可以用于减少特征空间维数、确定变量的线性组合、选择最有用的变量、变量辨识、识

日志 > 个人日记 转载到我空间 复制本文网址 隐藏签名档 小字体 选用该信纸上一篇|下一篇|返回日志列表设置置顶 | 编辑 | 删除单例模式（singleton）发表于：2008年2月22日 9时47分59秒阅读(3)评论(0)特效：[信纸]本文链接：http://user.qzone.qq.com/592433424/blog/1203644879

Wiki Ref: http://en.wikipedia.org/wiki/Lagrange_multipliersgeneral formulation: The weak Lagrangian principleDenote the objective function by and let the constraints be given by , perhaps by movi

Semi-Supervised:In computer science, semi-supervised learning is a class of machine learning techniques that make use of both labeled and unlabeled data for training - typically a small amount of la

 Original: http://en.wikipedia.org/wiki/Principal_component_analysis Example: http://www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf;                  http://download.csdn.ne

Exploring Spring ModelsBy Gustavo Oliveira GamasutraOctober 5, 2001URL: http://www.gamasutra.com/20011005/oliveira_01.htm  The first time I implemented a spring model, it fascinated me for hours