Open AccessLiver Disorderprognosis with Apache Spark Random Forest and Gradient Booster Algorithms
Author(s) -
Hari Krishna,
G Michael,
R. Kavitha,
Timmana Harikrishna,
C. Rajabhushanam
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i3123.0789s319
Subject(s) - random forest , booster (rocketry) , gradient boosting , boosting (machine learning) , alcohol consumption , population , medicine , algorithm , liver cancer , computer science , artificial intelligence , environmental health , cancer , biology , alcohol , engineering , biochemistry , aerospace engineering
Computerbecome an essential component in all the domains including Health care. Liver disorder is one of the extreme life threatening medical conditionthatcompete with cancer and leading death cause in US. More than 10 percent of the American population are affected by Liver disorders due to heavy alcohol consumption and unhealthy food habits. Prediction of liver disorders helps in patient diagnosis to increase the survival. In this paper, we analyze the liver disorder datasetGradient Boosting and Random Forest algorithm and compare their performance in terms of accuracy and error