Higher degree polynomial
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Description
I have a couple of questions about your paper "Polynomial Regression as an Alternative to Neural Networks".
- At point 5 it is said that "many authors recommend not using polynomial models of degree higher than 2 or 3" .
In which cases is it possible to get higher degree polynomials which fit well?
- At point 6.1 it is said that " the degree of the approximating polynomial increases from layer to layer".
So, if I get a polynomial of degree 3 which fits well, then the corresponding neural network will have three layers approximately?
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Research direction
Start by reading the paper's quoted sections, point 5 and point 6.1, and compare the claims about polynomial degree with the questions raised here. Done means clarifying when higher-degree polynomials may fit well and whether polynomial degree maps directly to neural-network layers, then updating the relevant explanation.
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Assessment
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100