Non-Standard Parameter Adaptation for Exploratory Data Analysis

• Main Authors: Barbakh, Wesam Ashour (Author), Wu, Ying (Author), Fyfe, Colin (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
• Series: Studies in Computational Intelligence, 249
• Subjects: Computer science.; Data mining.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Computer Science.; Data Mining and Knowledge Discovery.; Artificial Intelligence (incl. Robotics).; Appl.Mathematics/Computational Methods of Engineering.

Exploratory data analysis, also known as data mining or knowledge discovery from databases, is typically based on the optimisation of a specific function of a dataset. Such optimisation is often performed with gradient descent or variations thereof. In this book, we first lay the groundwork by revie...

Table of Contents:

• Review of Clustering Algorithms
• Review of Linear Projection Methods
• Non-standard Clustering Criteria
• Topographic Mappings and Kernel Clustering
• Online Clustering Algorithms and Reinforcement Learning
• Connectivity Graphs and Clustering with Similarity Functions
• Reinforcement Learning of Projections
• Cross Entropy Methods
• Artificial Immune Systems
• Conclusions.