KNN Hyperparameters

Optimize the hyperparameters of the scikit-learn K-Nearest Neighbors classifier. A custom training dataset can be used, and the features are standardized before training.

The searched hyperparameters are:

1. Number of neighbors.
2. Leaf size.

The weighting scheme (uniform or distance) is chosen on the form rather than searched. At least one hyperparameter must be selected for optimization.

The objective is to find the best set of hyperparameters that increases the classification accuracy.