Which algorithm is used in diabetes prediction?

Logistic Regression is one of the most common classification algorithms. The default value of C=1 provides with 78% accuracy on the training and 77% accuracy on the test set. Using C=0.01 results in lower accuracy on both the training and the test sets.

Logistic Regression is one of the most common classification algorithms. The default value of C=1 provides with 78% accuracy on the training and 77% accuracy on the test set. Using C=0.01 results in lower accuracy on both the training and the test sets.

Machine learning methods are widely used in predicting diabetes, and they get preferable results. Decision tree is one of popular machine learning methods in medical field , which has grateful classification power. Random forest generates many decision trees.