Improving Accuracy - Diabetes Classification

#1

How do I improve the accuracy of the K-NN approach for solving Diabetes Classification Challenge.

I can currently get 78% accuracy, with k = 13.

Also, in general, how can we improve the accuracy of a K-NN based system, barring increasing training data?

#2

Hey @Aayushhh, in this challenge using KNN you cannot achieve more than 78% accuracy.
In General, Wwth KNN , you can achieve a maximum accuracy of around 75-78%.
For that you can try the following :

  1. Find the best value of K for which the model performs best .
  2. Standardizing or normalizing your dataset.
  3. Averaging 2 or 3 different models predictions to get the final prediction.
  4. You can also try different distances like manhattan distance , minkowski distance , hamming distance etc.

If you want to achieve accuracy around 85-90% then you need to switch to some other algorithms which will be taught in the further contents of the course !

I hope this helps you clear your doubt !
Happy Learning. :slight_smile:

#3

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