• DOI:10.1007/978-3-642-17103-1_60
Corpus ID: 18901023

The Treatment of Missing Values and its Effect on Classifier Accuracy

@inproceedings{Acua2004TheTO,
  title={The Treatment of Missing Values and its Effect on Classifier Accuracy},
  author={E. Acu{\~n}a and C. Rodr{\'i}guez},
  year={2004}
}

E. Acuña, C. Rodríguez

Published 2004

Computer Science

The presence of missing values in a dataset can affect the performance of a classifier constructed using that dataset as a training sample. Several methods have been proposed to treat missing data and the one used most frequently deletes instances containing at least one missing value of a feature. In this paper we carry out experiments with twelve datasets to evaluate the effect on the misclassification error rate of four methods for dealing with missing values: the case deletion method, mean… CONTINUE READING

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