On Analyzing Milkey Way Globular Clusters: Comparing Efficiency of Dimension Reduction Techniques

By : Abisa Sinha Adhikary

Page No: 59-78

Abstract
Astronomical Data specifically those from Globular Clusters and Young Massive Clusters are usually contaminated with outliers and missing data, detection of which might be very tedious in case the data size is considerably large. Moreover, for skewed multivariate data, Principal Component Analysis (PCA) is not an appropriate approach for dimension reduction. The Robust Principal Component Analysis along with the Missing Value Imputation Technique using the MissForest algorithm is applied to a data from the Harris catalogue {Harris 2010} of globular clusters and the results are demonstrated with some striking features of the clusters.
 

Author :
Abisa Sinha Adhikary : Amity University, Kolkata, India
 

DOI: https://doi.org/10.32381/IAPQRT.2025.49.01.4