PREDICTIVE ANALYSIS OF OPIOD AND NON-OPIOD PRESCRIBER FOR IMPROVING ACCURACY USING IMPROVE XGBOOSTING SYSTEM
Abstract

Author(s): Anjali, Mr. Shivendra Dubey, Mr. Rakesh Shivhare, Mr. Mukesh Dixit

Tree boosting has exactly ended up being a profoundly e?ective way to deal with predictive modeling. It has indicated significant outcomes for an immense range of issues. We will demonstrate that XGBo ost utilizes a boosting calculation which we will use Newton boosting. This boosting calculation will additionally be contrasted and the gradient boosting calculation that MART utilizes. In addition, we will examine the regularization procedures that these strategies over along with these have on the models. We examine the XGBoost and Improved XGBoost claasifiers for both Opiod as well as Non – Opiod prescribers in terms of Accuracy and AUC score.