Classification Methodology for Symbolic Data (Wiley Series in Computational Statistics)De (autor) Lynne Billard, Edwin Diday
en Limba Engleză Carte Hardback – 02 Aug 2019
- Provides new classification methodologies for histogram valued data reaching across many fields in data science.
- Demonstrates how to manage a large complex dataset into manageable datasets ready for analysis.
- Features very large contemporary datasets such as time series, interval–valued data and histogram–valued data
- Considers classification models such as dynamical clustering, an extension of K–means, hierarchical pyramidal and Kohonen methodology in detail.
- Includes principal components and correspondence analysis methodology.
- Features a supporting website hosting relevant software.
- Edwin Diday is the founding father of Symbolic Data Analysis.
- Extends and expands on the material in Symbolic Data Analysis: Conceptual Statistics and Data Mining, Billard and Diday (2006)