The Bohachevsky1Function object to represent the Bohachevsky1 function for tests and benchmarks performed on function optimization and gradient descent classes.
The mathematical function that represents the gradient of the objective function represented by objFunction. An approximation using the Differential class is provided as the default implementation of this method, but it is highly encouraged to override this method with a hard-coded implementation of the correct gradient function in order to greatly improve the accuracy of the results.
The mathematical function that represents the gradient of the objective function represented by objFunction. An approximation using the Differential class is provided as the default implementation of this method, but it is highly encouraged to override this method with a hard-coded implementation of the correct gradient function in order to greatly improve the accuracy of the results.
The function described in this method implementation should correspond to the gradient of the function described in objFunction or else the results obtained in any tests or benchmarks will be void of meaning.
Value parameters
x
VectorD with the values of the variables to be used as input for the gradient function.
Attributes
Returns
VectorD The gradient of the objective function in the position given by the values in x.
The objective function used for benchmarking or testing purposes. Can be any mathematical function that receives an arbitrary number of real numbers as input and produces a single real number as an output.
The objective function used for benchmarking or testing purposes. Can be any mathematical function that receives an arbitrary number of real numbers as input and produces a single real number as an output.
Value parameters
x
VectorD with the values of the variables to be used as input for the objective function.
Attributes
Returns
Double The output of the objective function given by using the values in x as input.