# K-NN self-assessment questions:

**K-NN self-assessment questions:**

- Do I know the K-NN algorithm?
- Do I know the distance metrics used in K-NN for numerical, binary and discrete features?
- Do I know the effect of the values of K? Do I know the effect of outliers, noise, missing values and class imbalance on K-NN?
- Do I know the inductive bias of K-NN?
- Do I know what has to be done if features are on different scales before applying K-NN?
- Do I know how to compute the predictions when K-NN is used on a regression problem
- Do I know the effect of outliers, noise and missing values when using K-NN on a regression problem
- Could I apply the k-NN algorithm to a testing example given a training set?