1. A classification system comprising: a memory device; a processor communicatively connected to said memory device; and an input communicatively connected to said processor, wherein said input is configured to receive data comprising at least one object that is to be classified as one of an object of interest (OOI) and a nuisance of interest (NOI) based upon at least one non-Boolean attribute of said object; wherein said at least one object that is to be classified is at least one of a headlight from an oncoming vehicle and a tail light of a leading vehicle; wherein said OOI is said at least one object to be classified and said NOI is all other detected objects; wherein said processor is configured as a Bayesian classifier to classify said object based upon said non-Boolean attribute using a non-linear probability function; wherein said processor is further configured to determine a number of times said value of said non-Boolean attribute is within a threshold range for said OOI classification; and wherein said processor is further configured to determine a number of times said value of said non-Boolean attribute is within a threshold range for said NOI classification.
1. A classification system comprising: a memory device; a processor communicatively connected to said memory device; and an input communicatively connected to said processor, wherein said input is configured to receive data comprising at least one object that is to be classified as one of an object of interest (OOI) and a nuisance of interest (NOI) based upon at least one non-Boolean attribute of said object; wherein said at least one object that is to be classified is at least one of a headlight from an oncoming vehicle and a tail light of a leading vehicle; wherein said OOI is said at least one object to be classified and said NOI is all other detected objects; wherein said processor is configured as a Bayesian classifier to classify said object based upon said non-Boolean attribute using a non-linear probability function; wherein said processor is further configured to determine a number of times said value of said non-Boolean attribute is within a threshold range for said OOI classification; and wherein said processor is further configured to determine a number of times said value of said non-Boolean attribute is within a threshold range for said NOI classification. 2. The classification system of claim 1 , wherein said processor is further configured to combine a plurality of said non-Boolean attributes through multiplication to produce a probability of said object's classification.