Optimal tree led approach for effective decision making to mitigate mortality rates in a varied demographic dataset

摘要

Decision trees always have been a data structure of choice for taking decisions under various conditions and often provide elegant decision making to resolve complex conditional problems. Optimality is a condition under which parameters of interest have to either minimized or maximized. The principle of Pareto Optimality when applied to test the worth of solution nodes in a decision tree provide for a designated conditional approach to optimize the state reported in the solution nodes. In this paper, an effort has been made to test the leaf nodes of decision trees created by three different condition sets applied on a huge dataset having in excess of 106 entries with multiple attributes using Pareto Optimality principle. The results produced by Pareto Optimality Operator thus designed clearly demarcates the conditions under which the casualty rates can be minimized.