LWS related queries

#1
  1. What are the kind of practical use cases for locally weighted regression ?
  2. if my query point is out of the range of the training set x values, how will this algorithm work?

Thanks

#2

Hi @sanandasaha3

LOWESS is typically useful when the expected curve is non-linear and a single line (given by plain linear regression) cannot be used to describe the data accurately.
Another big advantage of LOWESS is the fact that it does not require the specification of a function to fit a model to all of the data in the sample. In addition, LOWESS is very flexible, making it ideal for modeling complex processes for which no theoretical models exist.

Coming to the second point, LOWESS is generally used where the samples are plenty and hence the probability of such a outlier are low. Even then, LOWESS still works because each point in the training data is still assigned a weight (it is small though) and the other equations too are still valid.

Hope this helps!

#3

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