一、特征选择
二、分类方法
三、决策树
四、人工神经网络与遗传算法
五、支持向量机
六、图论与聚类方法
其它（待补）
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一、特征选择
[PPT]Feature Selection for Classification
[PPT]Feature Selection for Classification M.Dash, H.Liu
[PPT]Classification and Feature Selection
[PPT]Feature Saliency in Unsupervised Learning
[PPT]Feature Selection/Extraction for Classification Problems
[PPT]Dynamic Integration of Data Mining Methods Using Selection in a ... [PPT]Data Visualization and Feature Selection: New Algorithms for ... [PPT]Robust feature selection by mutual information distributions
[PPT]Dimensions
[PPT]WEKKEM: a study in Fractal Dimension and Dimensionality Reduction 二、分类方法
[PPT]Taxonomy Classification
[PPT]Linear Methods for Classification
[PPT]Deive Statistics
[PPT]Combining Classical Statistics and Data Mining in Tactical ... [PPT]Enhanced classification using hyperlinks
[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]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、人工神经网络与遗传算法
[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]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 五、支持向量机
[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
六、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]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]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 Root ed ...
[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]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