When to Use Polynomial Regression Instead of Neural Networks
There are certain scenarios where polynomial regression are a better option over neural network.
- When the relationship between variables is relatively simple and can be approximated by a polynomial function without the need for complex transformations.
- When interpretability of the model is crucial, and stakeholders require a clear understanding of the relationships between variables.
- When computational resources are limited
- When the dataset already contains polynomial features or the relationship between variables can be easily captured by adding polynomial terms to the regression model.
- When we are dealing with a low dimension dataset.
Polynomial Regression vs Neural Network
In this article, we are going to compare polynomial regression and neural networks.
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