calculates pairwise distances between all substances in Eigen::MatrixXd input and saves them to Eigen::MatrixXd output.
If Kernel.weights is not empty, function Kernel.calculateWeightedDistanceMatrix() is used
Else if: Kernel.f=="" and Kernel.g="", the distance between two substances a and b is calculated as , with m=#descriptors
Else: distance is calculated as
calculates pairwise distance between all substances of m1 and m2 and saves them to Eigen::MatrixXd output.
If Kernel.weights is not empty, function Kernel.calculateWeightedDistanceMatrix() is used
Esle if: Kernel.f=="" and Kernel.g="", the distance between two substances a and b is calculated as , with m=#descriptors
Else: distance is calculated as
calculates pairwise distances between all substances in Eigen::MatrixXd input, weighted by the contribution of every descriptor (as encoded in Kernel.weights), and saves them to Eigen::MatrixXd output.
Distance between two substances a and b is calculated as , with m=#descriptors
calculates pairwise distances between all substances of m1 and m2, weighted by the contribution of every descriptor (as encoded in Kernel.weights), and saves them to Eigen::MatrixXd output.
Distance between two substances a and b is calculated as , with m=#descriptors
grid search for the best kernel parameters.
Grid search is done locally around the current kernel parameter value(s).
Parameters
opt
if ==1, Model.optitimizeParameters() is used in each step of grid search, optimizing the parameter of the Model in addition to those of the kernel.
step_width
the size of each step to be made
steps
the number of steps for grid search
recursions
number of recursions of grid search; in each recursion the step width is decreased by factor of 10 and searching is done in 20 steps around the values of the best kernel parameters determined in last recursion
Equation for distance function for calculation of kernel matrix.
Distance of two substances a and b is calculated as , with m=#descriptors
Use "x1" and "x2" in the String, e.g. "x1*x2"
Equation for distance function for calculation of kernel matrix.
Distance of two substances a and b is calculated as , with m=#descriptors
g determines what is to be done with the calculated "sum" over all elements (use "sum" in String); e.g. "sum^0.5" => euclidean distance if f=="x1*x2"