Analysis Of Decision Tree For Diabetes Prediction

— Data mining has from long been human beings friend and savior in numerous ways and one of the methods is through decision making. With increasing health issues polygenic disorder incorporates a modern-day scourge with millions round the world affected. Data mining is growing in connection to finding such globe unwellness issues through its tools. The following study proposes to use the UCI repository polygenic disorder dataset and generate call tree models for classification mistreatment LAD tree, NB tree and a Genetic J48 tree. The decision tree based classifier models study includes various parameters like computational overheads consumed, features, efficiency and accuracy and provides the results. This genetic J48 model accurately classifies the dataset compared with the opposite 2 models in terms of accuracy and speed.

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Analysis Of Decision Tree For Diabetes Prediction

Semantic Scholar · Medicine · 2019

Abstract

— Data mining has from long been human beings friend and savior in numerous ways and one of the methods is through decision making. With increasing health issues polygenic disorder incorporates a modern-day scourge with millions round the world affected. Data mining is growing in connection to finding such globe unwellness issues through its tools. The following study proposes to use the UCI repository polygenic disorder dataset and generate call tree models for classification mistreatment LAD tree, NB tree and a Genetic J48 tree. The decision tree based classifier models study includes various parameters like computational overheads consumed, features, efficiency and accuracy and provides the results. This genetic J48 model accurately classifies the dataset compared with the opposite 2 models in terms of accuracy and speed.

References (11)

10Decision tree discovery for the diagnosis type 2 diabetes2011 · IEEE, International conference on innovation in information technology

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