Towards Optimization of Boosting Models for Formation Lithology Identification

Algorithm 3

XGBoost algorithm, modified from [23].

(1)	Given . The number of iterations: M
(2)	Initialize
(3)	For to M:(a)Compute , and (b)Fit base model , .(c)Determine the leaf weight for the learnt structure with and (d)Update current model with previous model and the constrained ,
(4)	Calculate the final boosting model .