Published July 6, 2015 | Version v1

Classification of Incomplete Patterns Based on the Fusion of Belief Functions

Description

The influence of the missing values in the classification of incomplete pattern mainly depends on the context. In this paper, we present a fast classification method for incomplete pattern based on the fusion of belief functions where the missing values are selectively (adaptively) estimated. At first, it is assumed that the missing information is not crucial for the classification, and the object (incomplete pattern) is classified based only on the available attribute values.

Files

Paper_1570107777-fusion2015-pcr.pdf

Files (424.8 kB)

Name Size Download all
md5:260d805f295c8a8e235e05969e32361d
424.8 kB Preview Download