1. A method comprising: accessing a training set including a target object set and a clutter object set, the target object set including a target associated with a target feature value and the clutter object set including a non-target object associated with a clutter feature value; determining that the training set includes multiple types of targets or multiple types of clutter; comparing the target feature value of a type of target with the clutter feature value; associating the type of target with the non-target object based on the comparison; training a classifier using the target feature value and the clutter feature value of the associated type of target and the non-clutter object such that the classifier produces a metric that indicates that an object associated with the type of target is a target; generating multiple classifiers, the multiple classifiers including the trained classifier; applying a feature value associated with an unknown object to the multiple classifiers to generate a set of metrics for the unknown object; aggregating the metrics into an overall metric; and determining whether the unknown object is included in the target set based on the overall metric.