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Archive | Optimization

Response Surface of Objective Function With Sequence of Best Solutions Plotted as Black Dots

Stochastic Hill Climbing in Python from Scratch

Stochastic Hill climbing is an optimization algorithm. It makes use of randomness as part of the search process. This makes the algorithm appropriate for nonlinear objective functions where other local search algorithms do not operate well. It is also a local search algorithm, meaning that it modifies a single solution and searches the relatively local […]

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Plot of Second Degree Polynomial Fit to Economic Dataset

Curve Fitting With Python

Curve fitting is a type of optimization that finds an optimal set of parameters for a defined function that best fits a given set of observations. Unlike supervised learning, curve fitting requires that you define the function that maps examples of inputs to outputs. The mapping function, also called the basis function can have any […]

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