Advances in machine learning. I, Dedicated to the memory of Professor Ryszard S.Michalski
This is the first volume of a large two-volume editorial project we wish to dedicate to the memory of the late Professor Ryszard S. Michalski who passed away in 2007. He was one of the fathers of machine learning, an exciting and relevant, both from the practical and theoretical points of view, area...
保存先:
| 第一著者: | |
|---|---|
| その他の著者: | , , , |
| フォーマット: | Livre numérique |
| 言語: | Anglais |
| 出版事項: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| 版: | 1st ed. 2010. |
| シリーズ: | Studies in Computational Intelligence
262 |
| オンライン･アクセス: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| 注記: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Advances in Machine Learning I, Texte imprimé, 9783642051760 • Advances in Machine Learning I, Texte imprimé, 9783642052163 • Advances in Machine Learning I, Texte imprimé, 9783642051760 • Advances in Machine Learning I, Texte imprimé, 9783642262302 |
目次:
- Introductory Chapters Ryszard S. Michalski: The Vision and Evolution of Machine Learning The AQ Methods for Concept Drift Machine Learning Algorithms Inspired by the Work of Ryszard Spencer Michalski Inductive Learning: A Combinatorial Optimization Approach General Issues From Active to Proactive Learning Methods Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms Transfer Learning via Advice Taking Classification and Beyond Determining the Best Classification Algorithm with Recourse to Sampling and Metalearning Transductive Learning for Spatial Data Classification Beyond Sequential Covering Boosted Decision Rules An Analysis of Relevance Vector Machine Regression Cascade Classifiers for Hierarchical Decision Systems Creating Rule Ensembles from Automatically-Evolved Rule Induction Algorithms Structured Hidden Markov Model versus String Kernel Machines for Symbolic Sequence Classification Soft Computing Partition Measures for Data Mining An Analysis of the FURIA Algorithm for Fuzzy Rule Induction Increasing Incompleteness of Data Sets A Strategy for Inducing Better Rule Sets Knowledge Discovery Using Rough Set Theory Machine Learning Techniques for Prostate Ultrasound Image Diagnosis Segmentation of Breast Cancer Fine Needle Biopsy Cytological Images Using Fuzzy Clustering Machine Learning for Robotics Automatic Selection of Object Recognition Methods Using Reinforcement Learning Comparison of Machine Learning for Autonomous Robot Discovery Multistrategy Learning for Robot Behaviours Neural Networks and Other Nature Inspired Approaches Quo Vadis? Reliable and Practical Rule Extraction from Neural Networks Learning and Evolution of Autonomous Adaptive Agents Learning and Unlearning in Hopfield-Like Neural Network Performing Boolean Factor Analysis