Research Article
Application of a Mobile Chronic Disease Health-Care System for Hypertension Based on Big Data Platforms
Input: | Hypertension disease data set | Output: | Selected features and SVM classifier | 1. load data set | 2. Sample the data randomly into training (67%) and testing(33%) data set | 3. set target variable | 4. generate the classifier based on the training data set | 5. train the classifier using linear kernel function (similarity function) | 6. predict the testing data set using the trained classifier | 7. evaluate the classifier | 8. Recursively select the features correspond to their weights |
|