Name
Title | ||
|---|---|---|
Effects of Kurtosis for the Error Rate Estimators Using Resampling Methods in Two Class Discrimination |
Abstract | ||
|---|---|---|
In preceding studies, error rate estimators have been compared under various conditions and in most cases the population distribution was assumed to be normal. Effects of non-normality of the population have therefore not been studied sufficiently. In this study, we focused on kurtosis as a measure of non-normality and examined the effects of kurtosis for error rate estimators, especially resampling-based estimators. Our simulation results in two-class discrimination using a linear discriminant function suggest that it is necessary to consider non-normality of the population in comparison of estimators. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-04592-9_43 | KES (2) |
Keywords | Field | DocType |
two-class discrimination,linear discriminant function,resampling methods,class discrimination,resampling-based estimator,error rate estimator,simulation result,population distribution,various condition,error rate,bias,bootstrap,robustness,standard deviation | Population,Pattern recognition,Word error rate,Bootstrapping (statistics),Artificial intelligence,Linear discriminant analysis,Statistics,Standard deviation,Resampling,Mathematics,Kurtosis,Estimator | Conference |
Volume | ISSN | Citations |
5712 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kozo Yamada | 1 | 0 | 0.34 |
| Hirohito Sakurai | 2 | 0 | 0.68 |
| Hideyuki Imai | 3 | 103 | 25.08 |
| Yoshiharu Sato | 4 | 13 | 4.06 |