Name
Title | ||
|---|---|---|
Comparison of decision trees with Rényi and Tsallis entropy applied for imbalanced churn dataset |
Abstract | ||
|---|---|---|
Two algorithms for building classification trees, based on Tsallis and Rényi entropy, are proposed and applied to customer churn problem. The dataset for modeling represents highly unbalanced proportion of two classes, which is often found in real world applications, and may cause negative effects on classification performance of the algorithms. The quality measures for obtained trees are compared for different values of α parameter. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.15439/2015F121 | 2015 Federated Conference on Computer Science and Information Systems (FedCSIS) |
Keywords | Field | DocType |
decision trees,Renyi entropy,Tsallis entropy,imbalanced churn dataset,classification trees,customer churn problem | Decision tree,Data mining,Computer science,Rényi entropy,Tsallis entropy,Artificial intelligence,Statistical classification,Machine learning | Conference |
Volume | ISSN | Citations |
5 | 2300-5963 | 3 |
PageRank | References | Authors |
0.68 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Krzysztof Gajowniczek | 1 | 19 | 6.14 |
| Tomasz Zabkowski | 2 | 32 | 11.28 |
| Arkadiusz Orłowski | 3 | 20 | 11.73 |