模式识别中的机器学习与数据挖掘/Machine Learning and Data Mining in Pattern Recognition

作者： Petra Perner著

出 版 社： 北京燕山出版社

出版时间： 2005-12-1字数：版次： 1页数： 695印刷时间： 2005/12/01开本：印次：纸张： 胶版纸I S B N ： 9783540269236包装： 平装编辑推荐

The LNAI series reports state-of-the-art results in artificial intelligence re-search, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies,LNAI has grown into the most comprehensive artificial intelligence research forum available.

The scope of LNAI spans the whole range of artificial intelligence and intelli-gent information processing including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes

-proceedings (published in time for the respective conference)

-post-proceedings (consisting of thoroughly revised final full papers)

-research monographs (which may be based on PhD work)

内容简介

This book constitutes the refereed proceedings of the 4th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2005, held in Leipzig, Germany, in July 2005.

The 68 revised full papers presented were carefully reviewed and selected. The papers are organized in topical sections on classification and model estimation, neural methods, subspace methods, basics and applications of clustering, feature grouping, discretization, selection and transformation, applications in medicine, time series and sequential pattern mining, mining images in computer vision, mining images and texture, mining motion from sequence, speech analysis, aspects of data mining, text mining, and as a special track: industrial applications of data mining.

目录

Classification and Model Estimation

On ECOC as Binary Ensemble Classifiers

Incremental Classification Rules Based on Association Rules Using Formal Concept Analysis

Parameter Inference of Cost-Sensitive Boosting Algorithms

Finite Mixture Models with Negative Components

MML-Based Approach for Finite Dirichlet Mixture Estimation and Selection

Principles of Multi-kernel Data Mining

Neural Methods

Comparative Analysis of Genetic Algorithm, Simulated Annealing and Cutting Angle Method for Artificial Neural Networks

Determining Regularization Parameters for Derivative Free Neural Learning

A Comprehensible SOM-Based Scoring System

Subspace Methods

The Convex Subclass Method: Combinatorial Classifier Based on a Family of Convex Sets

SSC: Statistical Subspace Clustering

Understanding Patterns with Different Subspace Classification

Clustering: Basics

Using Clustering to Learn Distance Functions for Supervised Similarity Assessment

Linear Manifold Clustering

Universal Clustering with Regularization in Probabilistic Space

Acquisition of Concept Descriptions by Conceptual Clustering

Applications of Clustering

Clustering Large Dynamic Datasets Using Exemplar Points

Birds of a Feather Surf Together: Using Clustering Methods to Improve Navigation Prediction from Internet Log Files

Alarm Clustering for Intrusion Detection Systems in Computer Networks

Clustering Document Images Using Graph Summaries

Feature Grouping, Diseretization, Selection and Transformation

Feature Selection Method Using Preferences Aggregation

……

Applications in Medicine

Time Series and Sequential Pattern Mining

Mining Images in Computer Vision

Mining Images and Texture

Mining Motion from Sequence

Speech Analysis

Aspects of Data Mining

Text Mining

Special Track:Industrial Applecations of Data Mining

Author Index