Machine Learning

The K-neighbors method is an instance-based learning algorithm. It remembers the

training set and when a new data point is presented it looks for the closest K samples

from the training set and returns.

• the average of the target values of these K values for regression

• the class of the majority of the K training examples. (using some procedure to break ties)

Regularisation

The parameter K can be used to control over

• With K=1 the algorithm is likely to overfit.

• Large values of k can underfit

Example

We can use the iris dataset:

for k=1

for k=3

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