Advanced methods for missing values imputation based on similarity learning.

ABSTRACT: The real-world data analysis and processing using data mining techniques often are facing observations that contain missing values. The main challenge of mining datasets is the existence of missing values. The missing values in a dataset should be imputed using the imputation method to improve the data mining methods' accuracy and performance. There are existing techniques that use k-nearest neighbors algorithm for imputing the missing values but determining the appropriate k value can be a challenging task. There are other existing imputation techniques that are based on hard clustering algorithms. When records are not well-separated, as in the case of missing data, hard clustering provides a poor description tool in many cases. In general, the imputation depending on similar records is m

SUBMITTER: Fouad KM 

PROVIDER: S-EPMC8323724 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature