机器学习的相关材料

 

 壹 、特征选拔

ACM/ICPC在线题库集锦:

 二 、分类方法

网址:http://acm.uva.es/
简称: uva
全称: Valladolid Programming Contest Site
所在国:西班牙
付出格局:web格局和email格局
表达:也许是世界上名誉最大,最古老的在线题库了。收集了N卷
的题材,许多国家队的国手都以从那里练出来的。标题包含历届
ACM/ICPC分区赛试题、半决赛试题以及许多别的网上朋友本人出的题
目。标题类型比较完美,难度较平均,不过测试数据极度狡猾,
还要平时更新旧的数目,在别的地点能通过的先后到了uva就只怕
没辙透过。定期有比赛,并且能够运用它的系统主办自个儿的竞赛。
唯一的败笔是系统太烂,竞赛的时候平时系统崩溃(可是那和列席
的人太多也有关)。

三、决策树

网址:http://acm.zju.edu.cn/
简称: zju/zoj
全称: ZJU Online Judge Contests
所在国:中国
付给格局:web情势
证实:近日境内唯一3个在线题库。NJU的Settler队
重点就在那里锻炼,因为不用出国,很有益于。近期有
6卷题目了,标题大多数是原先的ACM/ICPC分区赛试
题和有个别浙大ACM队员本身出的难点。定期有比赛。

肆 、人工神经互联网与遗传算法

网址:http://acm.timus.ru/
简称: ural
全称: Ural State University Problem Set Archive with Online Judge
System
所在国:俄罗斯
付出形式:web格局和email格局
表明:那也是多少个有名的题库,因为是俄罗斯人办的,题目的数
学味道相比浓。定期有比赛。那里的标题风格和ACM/ICPC不太雷同,
标题数学趣味浓,有肯定难度,很多难题都是那种供给有个别小技巧的,
如果想出来了程序或者唯有几十行。中华夏族民共和国的成都百货上千搞OI的中学生在此地
做题,那里的题目相比较符合中学的OIer。

伍 、协助向量机

网址:http://acm.sgu.ru/
简称: sgu
全称: Saratov State University :: Online Contester
所在国:俄罗斯
交给情势:web情势
证实:三个比较新的题库,同样因为是俄罗丝人办的,标题标数学
寓意很浓。定期有比赛。

陆 、图论与聚类方法

以上那多少个是相比相符插足ACM/ICPC的同班训练用的题库,还有局地
诸如USACO等题库,基本上便是面向中学生的,这里就不提了。

其它(待补)

主导算法与数据结构普通话索引:

***********************************

Data Structures 基本数据结构
Dictionaries 字典
Priority Queues 堆
Graph Data Structures 图
Set Data Structures 集合
Kd-Trees 线段树
Numerical Problems 数值难点
Solving Linear Equations 线性方程组
Bandwidth Reduction 带宽压缩
Matrix Multiplication 矩阵乘法
Determinants and Permanents 行列式
Constrained and Unconstrained Optimization 最值难题
Linear Programming 线性规划
Random Number Generation 随机数变化
Factoring and Primality Testing 因子分解/质数判定
Arbitrary Precision Arithmetic 高精度计算
Knapsack Problem 背包难题
Discrete Fourier Transform 离散Fourier变换
Combinatorial Problems 组合难题
Sorting 排序
Searching 查找
Median and Selection 中位数
Generating Permutations 排列生成
Generating Subsets 子集生成
Generating Partitions 划分生成
Generating Graphs 图的扭转
Calendrical Calculations 日期
Job Scheduling 工程布署
Satisfiability 可满足性
Graph Problems — polynomial 图论-多项式算法
Connected Components 连通分支
Topological Sorting 拓扑排序
Minimum Spanning Tree 最小生成树
Shortest Path 最短路径
Transitive Closure and Reduction 传递闭包
Matching 匹配
Eulerian Cycle / Chinese Postman Euler回路/中华夏族民共和国邮路
Edge and Vertex Connectivity 割边/割点
Network Flow 网络流
Drawing Graphs Nicely 图的描写
Drawing Trees 树的描绘
Planarity Detection and Embedding 平面性检查和测试和放手
Graph Problems — hard 图论-NP问题
Clique 最大团
Independent Set 独立集
Vertex Cover 点覆盖
Traveling Salesman Problem 旅行商难题
Hamiltonian Cycle Hamilton回路
Graph Partition 图的细分
Vertex Coloring 点染色
Edge Coloring 边染色
Graph Isomorphism 同构
Steiner Tree Steiner树
Feedback Edge/Vertex Set 最大无环子图
Computational Geometry 总括几何
Convex Hull 凸包
Triangulation 三角剖分
Voronoi Diagrams Voronoi图
Nearest Neighbor Search 方今点对查询
Range Search 范围查询
Point Location 地方查询
Intersection Detection 碰撞测试
Bin Packing 装箱难点
Medial-Axis Transformation 中轴变换
Polygon Partitioning 多边形分割
Simplifying Polygons 多边形化简
Shape Similarity 相似多边形
Motion Planning 运动布置
Maintaining Line Arrangements 平面分割
Minkowski Sum Minkowski和
Set and String Problems 集合与串的题材
Set Cover 集合覆盖
Set Packing 集合配置
String Matching 格局匹配
Approximate String Matching 模糊匹配
Text Compression 压缩
Cryptography 密码
Finite State Machine Minimization 西周自动机简化
Longest Common Substring 最长公共子串
Shortest Common Superstring 最短公共父串

一 、特征选用

书:
算法类:
N. Wirth, Algorithms + Data Structures = Programs, Prentice-Hall,
Englewood Cl
iffs, 1975.

[PPT]Feature Selection for Classification

N. Wirth, Systematic Programming An Introduction, Prentice Hall, 1973.

[PPT]Feature Selection for Classification M.Dash, H.Liu

A. Engel, Exploring mathematics with your computer, The Mathematical
Associati
on of America, 1993.

[PPT]Classification and Feature Selection

H. Papadimitriou, K. Steigltz, Combinatorial optimization – Algorithms
and co
mplexity, Dover, PUBNS, 1998.

[PPT]Feature Saliency in Unsupervised Learning

A. Vitek, I. Tvrda i dr., Problems in programming / experience through
practic
e, John Wiley & Sons Ltd., 1991.

[PPT]Feature Selection/Extraction for Classification Problems

T. H. Cormen, C. E. Leiserson, R. L. Rivest, S. Stein, Introduction to
Algorit
hms, The MIT Press, 2001.

[PPT]Dynamic Integration of Data Mining Methods Using Selection in a

D. E. Knuth, The Art of Computer Programming, 2nd Edition,
Addison-Wesley, Vol
ume 1: Fundamental Algorithms, 1997.; Volume 2: Seminumerical
Algorithms, 1997
.; Volume 3: Sorting and Searching, 1998.

[PPT]Data Visualization and Feature Selection: New Algorithms for …

Z. Michalewicz, D. B. Fogel, How to Solve It: Modern Heuristics,
Springer-Verl
ag Berlin, 1999.

[PPT]Robust feature selection by mutual information distributions

Steven S. Skiena, The Algorithm Design Manual, Springer-Verlag New York,
Ins.,

[PPT]Dimensions

[PPT]WEKKEM: a study in Fractal Dimension and Dimensionality Reduction

A. Shen, Algorithms and Programming – Problems and Solutions, Birkh?user
Bosto
n, 1997.

贰 、分类方法 

总括机算法导引 机械

[PPT]Taxonomy Classification

赛题分析类:
ACM 试题分析(一)、(二)、(三) 吴文虎 哈工大
ACM 国际大学生程序设计竞赛入门 陈红山(拉巴斯) 机械出版
整合数学/图论/奥林匹克新闻学国内外赛题分析 吴文虎 王建德
ACM/ICPC 试题分析 王建德

[PPT]Linear Methods for Classification

理论类:
M. Sipser, Introduction to Theory of Computation.

[PPT]Descriptive Statistics

H. Lewis & C. Papadimitriou, Elements of the theory of computation.

[PPT]Combining Classical Statistics and Data Mining in Tactical …

J. Hopcroft, R. Motwani & J. Ullman. Introduction to Automata
Theory, Languages, and Computation.

[PPT]Enhanced classification using hyperlinks

原版的书文链接:http://evilcat.blogchina.com/4785061.html

[PPT]Classification Algorithms

[PPT]Classification

[PPT]Reading Report on “The Foundations of Cost-Sensitive Learning …

[PPT]Classification and Prediction (3)

[PPT]4.3 Classification of Fuzzy Relation

[PPT]Classification & Data Mining

[PPT]Machine learning for classification

[PPT]Heuristic Search

[PPT]Comparing Classification Methods

[PPT]A Practical Algorithm to Find the Best Episode Patterns

[PPT]Taxonomy of Data-Mining/Knowledge Discovery Tasks

[PPT]Mining Frequent Patterns Without Candidate Generation

 [PPT]KNOWLEDGE AND REASONING

[PPT]Comparisons of Capabilities of Data Mining Tools

[PPT]Uncertainty Reduction in Data Mining: A Case study for Robust …

[PPT]Visualizing and Exploring Data

[PPT]An Integrated Approach to Decision Making under Uncertainty UCLA

 

[PPT]Mining Unusual Patterns in Data Streams: Methodologies and …

[PPT]Learning: Nearest Neighbor

[PPT]Structured Principal Component Analysis

[PPT]Machine Learning through Probabilistic Models

[PPT]Advances in Bayesian Learning

[PPT]Using Discretization and Bayesian Inference Network Learning for

[PPT]Bayesian Optimization Algorithm, Decision Graphs, and Occam’s …

[PPT]Bayesian Inference

[PPT]Text Mining Technique Overview and an Application to Anonymous

[PPT]Improving Text Classification Accuracy by Augmenting Labeled …

[PPT]Text Mining Technique Overview and an Application to Anonymous

[PPT]Fast and accurate text classification

[PPT]On feature distributional clustering for text categorization

[PPT]Hierarchical Classification of Documents with Error Control

[PPT]lovebet体育官网,A Study of Smoothing Methods for Language Models Applied to …

  

三、决策树

[PPT]Decision Trees

[PPT]Decision Tree Classification

[PPT]Induction and Decision Trees

[PPT]AN INTRODUCTION TO DECISION TREES

[PPT]Decision Tree Construction

[PPT]Decision Tree Learning II

[PPT]Decision Tree Learning

[PPT]Decision trees and Rule-Based systems

[PPT]Learning with Identification Trees

[PPT]Decision Tree Post-Prunning Methods

[PPT]Decision Trees that Maximise Margins

[PPT]Introduction to Noise Handling in Decision Tree Induction

[PPT]A Fuzzy Decision Tree Induction Method for Fuzzy Data

[PPT]Fuzzy decision tree for continuous classification

[PPT]Artificial Intelligence Machine Learning I – Decision Tree …

[PPT]OCToo: A Decision Tree Program

 [PPT]Packet Classification using Hierarchical Intelligent Cuttings

[PPT]Rule Induction Using 1-R and ID3

[PPT]Inferring Rudimentary Rules

[PPT]Deriving Classification Rules

 

四 、人工神经互连网与遗传算法

[PPT]Neural Networks

[PPT]Artificial Neural Networks

[PPT]Neural Networks: An Introduction and Overview

[PPT]Evolving Multiple Neural Networks

[PPT]Introduction to Neural Networks

[PPT]Training and Testing Neural Networks

[PPT]Neuro-Fuzzy and Soft Computing

 [PPT]A Comparison of a Self-Organizing Neural Network Vs. Traditional

[PPT]Breast Cancer Diagnosis via Neural Network Classification

[PPT]Effective Data Mining Using Neural Networks

[PPT]Machine learning and Neural Networks

[PPT]Artificial Neural Networks in Image Analysis

[PPT]Neural Miner

[PPT]Minimal Neural Networks

[PPT]Learning with Perceptrons and Neural Networks

[PPT]Feature Selection for Intrusion Detection Using SVMs and ANNs

[PPT]Artificial Neural Networks: Supervised Models

[PPT]Optimal linear combinations of Neural Networks

[PPT]Artificial Neural Networks for Supervised Learning in Data Mining

[PPT]Neural Computing

[PPT]Using Neural Networks for Clustering on RSI data and Related …

[PPT]Classification and diagnostic prediction using artificial neural

[PPT]Continuous Hopfield network

[PPT]SURVEY ON ARTIFICIAL IMMUNE SYSTEM

 

[PPT]Data Mining with Neural Networks and Genetic Algorithms

[PPT]Fuzzy Systems, Neural Networks and Genetic Algorithms

[PPT]Evolving Multiple Neural Networks

[PPT]Genetic Algorithms

[PPT]Multi-objective Optimization Using Genetic Algorithms. …

[PPT]Performance of Genetic Algorithms for Data Classification

[PPT]Evolutionary Algorithms

[PPT]Basic clustering concepts and clustering using Genetic Algorithm

 

⑤ 、协理向量机

[PPT]Support Vector Machine

[PPT]Support Vector Machines ch1. The Learning Methodology

[PPT]Kernel “Machine” Learning

[PPT]Relevance Vector Machine (RVM)

[PPT]Texture Segmentation using Support Vector Machines

[PPT]Large Margin Classifiers and a Medical Diagnostic Application

[PPT]C4.5 and SVM

[PPT]Support Vector Machines Project

[PPT]Scaling multi-class SVMs using inter-class confusion

[PPT]Mathematical Programming in Support Vector Machines

 

6、图论与聚类方法

[PPT]Clustering Algorithms

[PPT]Data Clustering: A Review

[PPT]Identifying Objects Using Cluster and Concept Analysis

[PDF]Clustering Through Decision Tree Construction

[PPT]Concept Learning II

[PPT]Minimum Partitioning and Clustering Algorithms

[PPT]5. Partitioning

[PPT]Constrained Graph Clustering

[PPT]Bi-clustering and co-similarity of documents and words using …

[PPT]Biclustering of Expressoin Data

[PPT]Classification, clustering, similarity

[PPT]Clustering Using Random Walks

[PPT]Mining Association Rules

[PPT]An Overview of Clustering Methods

 

[PPT]Matching

[PPT]Faster Subtree Isomorphism

[PPT]Similarity Flooding

[PPT]Entangled Graphs Bipartite correlations in multipartite states

[PPT]Maximum Planar Subgraphs in Dense Graphs

[PPT]Matching in bipartite graphs

[PPT]Voting and Consensus Mechanisms

[PPT]Chapter 12 Assignments and Matchings

[PPT]Geometric Constraint Satisfaction Problem Adoption of algebraic

[PPT]The Weighted Clique Transversal Set Problem on Distance- …

[PPT]A Better Algorithm for Finding Planar Subgraph

[PPT]HyperCuP

[PPT]The Disjoint Set ADT

[PPT]Trees, Hierarchies, and Multi-Trees Craig Rixford IS 247 – …

[PPT]Hypergraph

[PPT]ADT Graph

 

[PPT][Kruksal’s Algorithm]

[PPT]Branch-and-Cut

[PPT]GRAPHS

[PPT]Graphs

[PPT]Trees

[PPT]Trees and Graphs

PPT]Graph Algorithms

[PPT]Graph Problems

[PPT]Shorter Path Algorithms

 [PDF]Trees General Trees A Connected Graph A tree Rooted Trees Rooted

[PPT]Chapter 2 Graphs and Independence

[PPT]Graph Algorithms (or, The End Is Near)

[PPT]Greedy Graphs

[PPT]Integrating Optimization and Constraint Satisfaction

[PPT]Conceptual Graphs

[PPT]Guiding Inference with Conceptual Graphs

[PPT]Graph-Based Concept Learning

[PPT]Graphs and Digraphs

[PPT]The Graph Abstract Data Type

[PPT]The ERA Data Model: Entities, Relations and Attributes

[PPT]Stack and Queue Layouts of Directed Acyclic Graphs: Part I

[PPT]Minimum Cost Spanning Trees

[PPT]Chapter 13. Redundancy Elimination

[PPT]Graph Structures and Algorithms

[PPT]Hamiltonian Graphs

[PPT]Hamiltonian Cycles and paths

[PPT]Multilevel Algorithms

[PPT]Greedy and Randomized Local Search

[PPT]Network Capabilities

[PPT]Petri Nets ee249 Fall 2000

[PPT]Petri Nets

[PPT]Extracting hidden information from knowledge networks

[PPT]Interconnect Verification 1

[PPT]Network Flow Approach

[PPT]Statistical Inference, Multiple Comparisons, Random Field Theory

[PPT]Computational Geometry

 

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