Classification of breast cancer recurrence based on imputed data: a simulation study
Abstract Several studies have been conducted to classify various real life events but few are in medical fields; particularly about breast recurrence under statistical techniques. To our knowledge, there is no reported comparison of statistical classification accuracy and classifiers’ discriminative...
Main Authors: | Rahibu A. Abassi, Amina S. Msengwa |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2022-12-01
|
Series: | BioData Mining |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13040-022-00316-8 |
Similar Items
-
Outcome-sensitive multiple imputation: a simulation study
by: Evangelos Kontopantelis, et al.
Published: (2017-01-01) -
The Effects of Missing Data Characteristics on the Choice of Imputation Techniques
by: Oyekale Abel Alade, et al.
Published: (2020-05-01) -
Handling Planned and Unplanned Missing Data in a Longitudinal Study
by: Caron-Diotte, Mathieu, et al.
Published: (2023-06-01) -
Accuracy of random-forest-based imputation of missing data in the presence of non-normality, non-linearity, and interaction
by: Shangzhi Hong, et al.
Published: (2020-07-01) -
Managing missing items in the Fagerström Test for Nicotine Dependence: a simulation study
by: Shannon L. Gutenkunst, et al.
Published: (2022-05-01)