**Rough set data analysis: A road to non-invasive knowledge discovery**

by Ivo Düntsch, Günther Gediga

**Publisher**: Methodos Publishers (UK) 2000**ISBN/ASIN**: 190328001X**ISBN-13**: 9781903280010**Number of pages**: 108

**Description**:

This is not the first book on rough set analysis and certainly not the first book on knowledge discovery algorithms, but it is the first attempt to do this in a non-invasive way. In this book the authors present an overview of the work they have done in the past seven years on the foundations and details of data analysis. It is a look at data analysis from many different angles, and the authors try not to be biased for - or against - any particular method. This book reports the ideas of the authors, but many citations of papers on Rough Set Data Analysis in knowledge discovery by other research groups are included as well.

Download or read it online for free here:

**Download link**

(1.1MB, PDF)

## Similar books

**Introduction to Soft Computing**

by

**Eva Volna**-

**Bookboon**

This book gives an introduction to Soft Computing, which aims to exploit tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve close resemblance with human like decision making.

(

**6018**views)

**Essentials of Theoretical Computer Science**

by

**F. D. Lewis**-

**University of Kentucky**

This text is a broad introduction to the field, presented from a computer science viewpoint for computer scientists. This was designed to be used in a one-semester course for senior computer science majors or first year masters students.

(

**11035**views)

**Building Blocks for Theoretical Computer Science**

by

**Margaret M. Fleck**-

**University of Illinois, Urbana-Champaign**

This book provides a survey of basic mathematical objects, notation, and techniques useful in later computer science courses. It gives a brief introduction to some key topics: algorithm analysis and complexity, automata theory, and computability.

(

**8799**views)

**Computational and Inferential Thinking: The Foundations of Data Science**

by

**Ani Adhikari, John DeNero**-

**GitBook**

Data Science is about drawing useful conclusions from large and diverse data sets through exploration, prediction, and inference. Our primary tools for exploration are visualizations and descriptive statistics, for prediction are machine learning ...

(

**5327**views)