Clustering algorithm to approximate functions

[admin]

The strategy is very easy to describe:

1. Divide the domain of your function in k sub intervals.

2. Initialize k monomials;

3. Consider the monomials as centroids of your clustering algorithm.

4. Assign the points of the function to each monomial in compliance to the cluster ago.

5. Use the gradient descent to adjust the parameters of each monomial.

6. Go to 4. until the accuracy is good enough.

Read the entire post at:…





More blog entries from AnalyticBridge...