Name
Title | ||
|---|---|---|
Predicting the Relationship Between the Size of Training Sample and the Predictive Power of Classifiers |
Abstract | ||
|---|---|---|
The main objective of this paper is to investigate the relationship between the size of training sample and the predictive power of well-known classification techniques. We first display this relationship using the results of some empirical studies and then propose a general mathematical model which can explain this relationship. Next, we validate this model on some real data sets and found that the model provides a good fit to the data. This model also allow a more objective determination of optimum training sample size in contrast to current training sample size selection approaches which tend to be ad hoc or subjective. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-30134-9_71 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
statistical theory | Data set,Predictive power,Computer science,Artificial intelligence,Statistical theory,Machine learning,Empirical research,Sample size determination | Conference |
Volume | ISSN | Citations |
3215 | 0302-9743 | 6 |
PageRank | References | Authors |
0.48 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Natthaphan Boonyanunta | 1 | 6 | 0.81 |
| Panlop Zeephongsekul | 2 | 144 | 19.11 |