A Comparison of Strategies for Handling Missing Values in Rule Learning
| Type of publication: | Techreport |
| Citation: | jf:TUD-KE-2009-03 |
| Number: | TUD-KE-2009-03 |
| Year: | 2009 |
| Institution: | TU Darmstadt, Knowledge Engineering Group |
| URL: | /publications/reports/tud-ke-2009-03.pdf |
| Abstract: | In this paper, we review possible strategies for handling missing values in separate-and-conquer rule learning algorithms, and compare them experimentally on a large number of datasets. In particular through a careful study with data with controlled levels of missing values we get additional insights on the strategies’ different biases w.r.t. attributes with missing values. Somewhat surprisingly, a strategy that implements a strong bias against the use of attributes with missing values, exhibits the best average performance on 24 datasets from the UCI repository. |
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