In k-NN what will happen when you increase/decrease the value of k?
What is the smoothness of boundary? Can you please explain how we can create boundary in case of K-NN?
Hey @tisandas2011, in lay man terms smoothness of boundary is something like the boundaries separating different classes, must be smooth, and must not contains spikes.
In neural network videos, we will use a file named visualize.py it will help you to plot such decission boundaries.
Now suppose if k =1 than there will be huge impact of outliers. Which means outlliers will affect the decission boundary a lot, on the other hand if k=5 or any other little higher value than the impact of the outliers will be reduced. So the points which are very close to the outlier point, will be classified correctly.
Hope this resolved your doubt.
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