Missing data imputation framework for early childhood longitudinal data: a study case on NCDRC data
This research aims to develop an imputation framework for the National ChildhoodDevelopment Research Centre (NCDRC)s missing data. Missing data and other associatedissues, such as outliers, time points, noise, and continuity, were the main challenges in thisresearch. The nature of the NCDRC dataset...
Saved in:
Main Author: | Al-Amoodi, Abdullah Hussien Abdullah |
---|---|
Format: | thesis |
Language: | eng |
Published: |
2019
|
Subjects: | |
Online Access: | https://ir.upsi.edu.my/detailsg.php?det=6762 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Robust Random Regression Imputation method for missing data in the presence of outliers
by: John, Ahamefule Happy
Published: (2013) -
An improved K-nearest neighbor with grasshopper optimization algorithm for missing data imputation /
by: Nadzurah Zainal Abidin
Published: (2020) -
Enhanced k-nearest neighbours classification performance based on segmentation and imputation of missing data
by: Saeed, Soobia
Published: (2022) -
An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data
by: Samat, Nurul Ashikin
Published: (2017) -
An enhanced robust association rules method for missing values imputation in Arabic language data set
by: Salem, Awsan Thabet
Published: (2023)