Classifier performance and map accuracy

被引:65
作者
Richards, JA
机构
[1] School of Electrical Engineering, University College, University of New South Wales, Canberra, ACT
[2] School of Electrical Engineering, University College, University of New South Wales, Canberra
关键词
D O I
10.1016/0034-4257(96)00038-7
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The distinction between the performance of a classifier and the accuracy of the resulting thematic map is discussed. Sampling the map itself is recommended as the preferred method for testing its accuracy. It is shown, nonetheless, that map accuracy can also be determined from the performance of a classifier, as assessed from testing data, provided the prior probabilities of class membership are well estimated. Unfortunately, that is rarefy done in practice so that errors are often made in reported map accuracy figures if they are inferred from classifier behavior. Examples are presented to illustrate how an apparently well-behaved classifier can give poor results for certain classes, because of the proportions of those classes in the region being imaged.
引用
收藏
页码:161 / 166
页数:6
相关论文
共 12 条
[1]  
ABRAMSON N, 1963, INFORMATION THEORY C
[2]  
CARD DH, 1982, PHOTOGRAMM ENG REM S, V48, P431
[3]   A REVIEW OF ASSESSING THE ACCURACY OF CLASSIFICATIONS OF REMOTELY SENSED DATA [J].
CONGALTON, RG .
REMOTE SENSING OF ENVIRONMENT, 1991, 37 (01) :35-46
[4]  
FITZPATRICKLINS K, 1981, PHOTOGRAMM ENG REM S, V47, P343
[5]  
HORD RM, 1976, PHOTOGRAMM ENG REM S, V42, P671
[6]  
HUDSON WD, 1987, PHOTOGRAMM ENG REM S, V53, P421
[7]  
JANSSEN LLF, 1994, PHOTOGRAMM ENG REM S, V60, P419
[8]  
Richards J.A., 1993, REMOTE SENSING DIGIT
[9]   CONFIDENCE IN THE RESULTS OF LEARNING MACHINES TRAINED ON MASS-SPECTRA [J].
RICHARDS, JA ;
GRIFFITHS, AG .
ANALYTICAL CHEMISTRY, 1979, 51 (09) :1358-1361
[10]  
ROSENFIELD GH, 1982, PHOTOGRAMM ENG REM S, V48, P131