A Study of Machine-Learning Classifiers for Hypertension Based on Radial Pulse Wave
The importance of the classification variables features. The bar charts (a), (b), and (c) represent the results of feature importance of AdaBoost, Gradient Boosting, and Random Forest (RF), respectively. The y-axis represents the value of the importance for variables features. Note that “yes" represents that K-means is used to reduce noise in this model and vice versa.
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