VPtarget

VPtarget is a term used in computational fields to denote a target vector or desired outcome used in model training, evaluation, or control systems. It is not a standardized term with a single universal definition; its exact meaning varies by discipline.

In supervised learning with multi-dimensional outputs, VPtarget represents the true output vector y that models aim to predict. In control theory or trajectory planning, VPtarget may refer to the desired state or position that a system should reach.

In optimization contexts, VPtarget is used alongside VPinput or decision variables to formulate objective functions, typically through loss or cost functions measuring the discrepancy between the predicted or achieved vector and the VPtarget, such as squared error or other norms.

Variants include discrete VPtarget, where components take discrete values, and continuous VPtarget for real-valued targets. In time-dependent tasks, a VPtarget may be specified per time step or horizon.

The term's usage is context-dependent; readers should consult domain-specific literature when encountering VPtarget. There is no single canonical definition.