TD_NonLinearCombineTransform generates the values of a feature using the specified formula from the TD_NonLinearCombineFit function output.
A non-linear combination transform is a mathematical function that takes one or more input variables and combines them using a non-linear mathematical formula to generate an output variable. The relationship between the input variables and the output variable is not a linear relationship.
In contrast to linear transformations, where the output variable is a linear combination of the input variables, non-linear transformations can capture more complex relationships between variables, such as curves, bends, and interactions. Non-linear transformations are commonly used in machine learning and data analysis to capture non-linear patterns in data.
An example of a non-linear combination transform is the polynomial regression model, which uses a polynomial function to fit a non-linear relationship between the input variables and the output variable. Another example is the sigmoid function, which is often used in neural networks to introduce non-linearities into the model.