A Comparison of Five Methods for Missing Value Imputation in Data Sets

Yıl 2018, Cilt: 2 Sayı: 2, 80 - 85, 31.12.2018

Pınar Cihan

Öz

The missing values in the data sets do not allow for accurate analysis. Therefore, the correct imputation of missing values has become the focus of attention of researchers in recent years. This paper focuses on a comparison of most reliable and up to date estimation methods to imputing the missing values. Imputation of missing values has a very high priority because of its impact on next pre-processing, data analysis, classification, clustering, etc. Root mean square error (RMSE) value, classification accuracy and execution time are used to evaluate the performances of most popular five methods (mean, k-nearest neighbors, singular value decomposition, bayesian principal component analysis and missForest). When RMSE and classification accuracy values of methods were compared, it has observed that missForest method outperformed other methods in all datasets.

Anahtar Kelimeler

Missing value imputation, k-nearest neighbor, singular value decomposition, bayesian principal component analysis, missForest

A Comparison of Five Methods for Missing Value Imputation in Data Sets

Öz

The
missing values in the data sets do not allow for accurate analysis. Therefore,
the correct imputation of missing values has become the focus of attention of
researchers in recent years. This paper focuses on a comparison of most
reliable and up to date estimation methods to imputing the missing values.
Imputation of missing values has a very high priority because of its impact on
next pre-processing, data analysis, classification, clustering, etc. Root mean
square error (RMSE) value, classification accuracy and execution time are used
to evaluate the performances of most popular five methods (mean, k-nearest
neighbors, singular value decomposition, bayesian principal component analysis
and missForest). When RMSE and classification accuracy values of methods were
compared, it has observed that missForest method outperformed other methods in all
datasets.

Anahtar Kelimeler

Missing value imputation, k-nearest neighbor, singular value decomposition, bayesian principal component analysis, missForest

Kaynakça

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