void SOGP::init(unsigned int state_dim, unsigned int output_dim,
Kernel &kernel,
double noise,
double epsilon,
unsigned int capacity,
int problem_type,
int deletion_criteria
) {
this->kernel = kernel.createCopy();
this->state_dim = state_dim;
this->output_dim = output_dim;
this->noise = noise;
this->epsilon = epsilon;
this->capacity = capacity;
this->current_size = 0;
this->problem_type = problem_type;
this->deletion_criteria = deletion_criteria;
if ((this->problem_type != SOGP::CLASSIFICATION) && (this->problem_type != SOGP::REGRESSION)) {
throw OTL::OTLException("The problem has to be of SOGP::CLASSIFICATION or SOGP::REGRESSION");
}
if ((this->deletion_criteria != SOGP::NORM) && (this->deletion_criteria != SOGP::MINIMAX)) {
throw OTL::OTLException("The deletion criteria has to be either SOGP::NORM or SOGP::MINIMAX");
}
if (this->problem_type == SOGP::CLASSIFICATION) {
if (this->output_dim < 1) {
throw OTL::OTLException("You need at least one class for classification");
}
}
//initialise the matrices : not that the capacity is +1 since
//we allow it to grow one more before reducing.
this->alpha = MatrixXd::Zero(this->capacity+1, this->output_dim);
this->C = MatrixXd::Zero(this->capacity+1, this->capacity+1);
this->Q = MatrixXd::Zero(this->capacity+1, this->capacity+1);
this->initialized = true;
}
