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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Symbolic Data Analysis: Conceptual Statistics and Data Mining

Symbolic Data Analysis: Conceptual Statistics and Data Mining

Billard, Lynne
Diday, Edwin

Hardcover

Series: Wiley Computational Statistics

Probability & Statistics

ISBN10: 0470090162
ISBN13: 9780470090169
Publisher: Wiley
Published: Jan 16 2007
Pages: 336
Weight: 1.35
Height: 0.92 Width: 6.52 Depth: 9.05
Language: English
With the advent of computers, very large datasets have become routine. Standard statistical methods don't have the power or flexibility to analyse these efficiently, and extract the required knowledge. An alternative approach is to summarize a large dataset in such a way that the resulting summary dataset is of a manageable size and yet retains as much of the knowledge in the original dataset as possible. One consequence of this is that the data may no longer be formatted as single values, but be represented by lists, intervals, distributions, etc. The summarized data have their own internal structure, which must be taken into account in any analysis.

This text presents a unified account of symbolic data, how they arise, and how they are structured. The reader is introduced to symbolic analytic methods described in the consistent statistical framework required to carry out such a summary and subsequent analysis.

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