K-NN self-assessment questions:

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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?

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