I have a very large panel data and would like to apply a number of simple machine learning techniques in Matlab (Logistic Regression, Decision Trees, Bagged Trees).

During my preparation I came across fitglm and fitLifetimePDModel, the latter of which is meant to capture panel data. I was trying to understand how/if that differs from fitglm because when I try the below, the results are exactly the same.

Why is that? For example, under fitglm I'm not telling the program that each customer can have more than one data points.

load RetailCreditPanelData.mat

pdModel_1 = fitLifetimePDModel(data,"Logistic", 'AgeVar','YOB', 'IDVar','ID', 'LoanVars','ScoreGroup','ResponseVar','Default');
disp(pdModel_1.Model)

pdModel_2 = fitglm(data,'Default ~ 1 + ScoreGroup + YOB', 'Distribution','binomial', 'link', 'logit');
disp(pdModel_2)