1. A method for classifying defects using a defect review apparatus, comprising: obtaining an image of a defect on a sample using one of an electron type image detector and an optical image detector; extracting a characteristic of the defect from the image using a characteristic extractor; and classifying the defect in accordance with the extracted characteristic, and based on a rule-based classification and a learning type classification, wherein the step of classifying further comprises: calculating a set of first likelihoods of the defect belonging to each of a plurality of defect classes of the rule-based classification, by use of the extracted characteristic using a likelihood function which applies a plurality of if-then rules to calculate an index corresponding to a degree of probability that the defect belongs to a particular defect class; calculating a set of second likelihoods of the defect belonging to each of a plurality of defect classes of the learning type classification, by use of the extracted characteristic, wherein the learning type classification determines a distance to a center of a normal distribution of data for each defect class; calculating a third set of likelihoods of the defect belonging to each of the defect classes of the learning type classification and/or the defect classes of the rule-based classification, by use of the first and second likelihoods; and classifying the defect by use of the third likelihoods; and wherein the rule-based classification and learning type classification are present in a parallel relationship with each other and independent of each other.