Improving the accuracy of prediction of heart disease risk based on ensemble classification techniques
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Abstract
Machine learning involves artificial intelligence, and it is used in solving many problems in data science. One common application of machine learning is the prediction of an outcome based upon existing data. The machine learns patterns from the existing dataset, and then applies them to an unknown dataset in order to predict the outcome. Classification is a powerful machine learning technique that is commonly used for prediction. Some classification algorithms predict with satisfactory accuracy, whereas others exhibit a limited accuracy. This paper investigates a method termed ensemble classification, which is used for improving the accuracy of weak algorithms by combining multiple classifiers. Experiments…
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625
total citations
- FWCI
- 91.91
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- 100%
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Authors
2Topics & keywords
Topics
Keywords
- Machine learning
- Boosting (machine learning)
- Ensemble learning
- Artificial intelligence
- Computer science
- Feature selection
- Random forest
- Ensemble forecasting
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