[Retracted] Intelligent CO₂ Monitoring for Diagnosis of Sleep Apnea Using Neural Cryptography Techniques

Algorithm 2

KNN algorithm.

Step 1. Split the data set into the training and testing data sets and consider training sample data set . And the category of sample . And testing sample data .

Step 2. Take the initial value and choose the initial nearest neighbour to .

Step 3. Evaluate the distance between the test data set and all other training data set values.

Step 4. Sort the output distance values in ascending order and select the appropriate value.

Step 5. Choose the closest known sample values.

Step 6. Count the sample of categories with the highest probability within the known sample values.

Step 7. Implement the category of test sample data value as the category obtained by statistics using Step 6.