| This thesis focuses on clustering fifteen Zernike coefficients using the methods of clustering through linear regression models (CLM). Maximum likelihood approach is used to infer the parameters for each cluster. Bayesian information criterion (BIC) combined with Bootstrapped maximum volume (BMV) criterion are used to determine the number of clusters. The Bootstrap method is used to estimate the uncertainty on the number of clusters. These fifteen Zernike coefficients are clustered into four clusters with a 90% confidence interval of the number of clusters being (2, 5). |
