ID  - jf:TUD-KE-2009-03
T1  - A Comparison of Strategies for Handling Missing Values in Rule Learning
A1  - Wohlrab, Lars
A1  - FĂĽrnkranz, Johannes
Y1  - 2009
IS  - TUD-KE-2009-03
T2  - TU Darmstadt, Knowledge Engineering Group
UR  - http://www.ke.tu-darmstadt.de/publications/reports/tud-ke-2009-03.pdf
N2  - 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.
ER  -