Univariate Function Optimization in Python
How to Optimize a Function with One Variable?
Univariate function optimization involves finding the input to a function that results in the optimal output from an objective function.
This is a common procedure in machine learning when fitting a model with one parameter or tuning a model that has a single hyperparameter.
An efficient algorithm is required to solve optimization problems of this type that will find the best solution with the minimum number of evaluations of the objective function, given that each evaluation of the objective function could be computationally expensive, such as fitting and evaluating a model on a dataset.
This excludes expensive grid search and random search algorithms and in favor of efficient algorithms like Brent’s