Jets are excellent probes for the study of the deconfined matter formed in heavy ion collisions. The interaction of jets produced in relativistic heavy-ion collisions with the quark-gluon plasma
(QGP), lead to effects such as a suppression of jet yields at high 𝑝T and modification of internal jet structure that are used to constrain the properties of the QGP. This report shows the nuclear modification factor measurements of full jets in Pb-Pb collisions at √𝑠NN = 5.02 TeV recorded by the ALICE detector. In Pb-Pb collisions, accessing low 𝑝T jets is important because the lower 𝑝T jets are more strongly suppressed. However, it is very difficult to estimate the accurate background and reduce fluctuation in the low 𝑝T region. In this study, the background is estimated with two methods: an area based method and using machine learning (ML) techniques . The ML estimator enables to access lower transverse momenta and larger jet radii than that in the area based method. The potential bias introduced by the ML method is investigated and its impact is quantified.