Heart Disease Prediction Using Machine Learning Model Ensemble-Random Forest with Simple Regression
نویسندگان
چکیده
منابع مشابه
Optimal Spatial Prediction Using Ensemble Machine Learning.
Spatial prediction is an important problem in many scientific disciplines. Super Learner is an ensemble prediction approach related to stacked generalization that uses cross-validation to search for the optimal predictor amongst all convex combinations of a heterogeneous candidate set. It has been applied to non-spatial data, where theoretical results demonstrate it will perform asymptotically ...
متن کاملPrediction of Chronic Kidney Disease Using Random Forest Machine Learning Algorithm
The healthcare industry is producing massive amounts of data which need to be mine to discover hidden information for effective prediction, exploration, diagnosis and decision making. Machine learning techniques can help and provides medication to handle this circumstances. Moreover, Chronic Kidney Disease prediction is one of the most central problems in medical decision making because it is o...
متن کاملHypertension Prediction in Primary School Students Using an Ensemble Machine Learning Method
Introduction: The prevalence of hypertension in children is increasing, and this complication is considered the most important risk factor for cardiovascular diseases in older age. Early detection and control of hypertension can prevent its progress and reduce its consequences. Machine learning methods can help predict this complication promptly and reduce cost and time. This study aimed to pro...
متن کاملHypertension Prediction in Primary School Students Using an Ensemble Machine Learning Method
Introduction: The prevalence of hypertension in children is increasing, and this complication is considered the most important risk factor for cardiovascular diseases in older age. Early detection and control of hypertension can prevent its progress and reduce its consequences. Machine learning methods can help predict this complication promptly and reduce cost and time. This study aimed to pro...
متن کاملApplication of ensemble learning techniques to model the atmospheric concentration of SO2
In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and re...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Advanced Trends in Computer Science and Engineering
سال: 2020
ISSN: 2278-3091
DOI: 10.30534/ijatcse/2020/375942020