Dimension Reduction and Data Compression

2004 ◽  
pp. 81-105
Author(s):  
Jorge E. Hurtado

Author(s):  
Patricia E.N. Lutu

In data mining, sampling may be used as a technique for reducing the amount of data presented to a data mining algorithm. Other strategies for data reduction include dimension reduction, data compression, and discretisation. For sampling, the aim is to draw, from a database, a random sample, which has the same characteristics as the original database. This chapter looks at the sampling methods that are traditionally available from the area of statistics, how these methods have been adapted to database sampling in general, and database sampling for data mining in particular.



Author(s):  
Patricia E.N. Lutu

In data mining, sampling may be used as a technique for reducing the amount of data presented to a data mining algorithm. Other strategies for data reduction include dimension reduction, data compression, and discretisation. For sampling, the aim is to draw, from a database, a random sample, which has the same characteristics as the original database. This chapter looks at the sampling methods that are traditionally available from the area of statistics, how these methods have been adapted to database sampling in general and database sampling for data mining in particular.







2009 ◽  
Author(s):  
Christopher J. C. Burges


1986 ◽  
Author(s):  
E. Gordon ◽  
B.O. Lehmann ◽  
C.A. Stacklin




Sign in / Sign up

Export Citation Format

Share Document