2013 | Action Number: IC0702
Studies in Fuzziness and Soft Computing: Towards Advanced Data Analysis by Combining Soft Computing and Statistics
- Pages: 378
- Author(s): C. borgelt, M.A. Gil, J. M.C. Sousa, M. Verleysen (Eds)
- Publisher(s): Springer
- ISBN/ISSN: 978-3-642-30278-7
- EUR: 139.05
- The book aims to describe how soft computing and statical methods can be used together to improve data analysis
- Advances research in soft computing and statical methods for data analysis
- Written by leading experts in the field
Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasise different aspects of data analysis.
Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasises the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty.
Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analysing the possible situations and their (relative) likelihood. It emphasises the need for mathematical methods and tools to assess solutions and guarantee performance.
Combining the two fields enhances the robustness and generalisability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.