Predicting metabolic syndrome using decision tree and support vector machine methods
<div><div><div><p><strong>BACKGROUND:</strong> Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose in...
Main Authors: | Farzaneh Karimi-Alavijeh, Saeed Jalili, Masoumeh Sadeghi |
---|---|
Format: | Article |
Language: | English |
Published: |
Vesnu Publications
2016-06-01
|
Series: | ARYA Atherosclerosis |
Subjects: | |
Online Access: | http://arya.mui.ac.ir/index.php/arya/article/view/967 |
Similar Items
-
CLASSIFICATION OF ENTREPRENEURIAL INTENTIONS BY NEURAL NETWORKS, DECISION TREES AND SUPPORT VECTOR MACHINES
by: Marijana Zekić-Sušac, et al.
Published: (2010-12-01) -
Prediction of Bradycardia using Decision Tree Algorithm and Comparing the Accuracy with Support Vector Machine
by: Devisetty Gowtham, et al.
Published: (2023-01-01) -
Model for the Prediction of Dropout in Higher Education in Peru applying Machine Learning Algorithms: Random Forest, Decision Tree, Neural Network and Support Vector Machine
by: Omar A Jimenez, et al.
Published: (2023-05-01) -
COMPARATION OF DECISION TREE MODEL AND SUPPORT VERCTOR MACHINE IN SENTIMENT ANALYSIS OF REVIEW DATASET SAMSUNG SSD 850 EVO AT NEW EGG SHOP
by: Muhammad Fahmi Julianto, et al.
Published: (2021-09-01) -
Efficient Decision Trees for Multi–Class Support Vector Machines Using Entropy and Generalization Error Estimation
by: Kantavat Pittipol, et al.
Published: (2018-12-01)