1. A computer implemented method for classifying a document using a plurality of confidence grades, comprising: training a classifier using a plurality of training documents, comprising: obtaining a list of first words from said training documents, wherein each of the training documents is classified into one of a plurality of classes; for each class belonging to said classes: determining a prior probability of said class, wherein said prior probability is probability of occurrence of said training documents in said class given said training documents in said classes; calculating conditional probabilities for said list of first words; determining a plurality of confidence thresholds using said list of first words, said prior probability of said class, and one of a plurality of threshold constants; defining said confidence grades using said determined confidence thresholds; and classifying said document using said trained classifier, comprising: obtaining a list of second words from said document, wherein said second words are commonly present in said list of first words; determining conditional probabilities for said list of second words for each of said classes from said calculated conditional probabilities for said list of first words; calculating a posterior probability for each of said classes using said prior probability and said determined conditional probabilities; comparing said calculated posterior probability with said determined confidence thresholds for each of said classes; assigning each of said classes to one of said defined confidence grades based on said comparison of said calculated posterior probability with said determined confidence thresholds; and assigning said document to one of said classes based on said calculated posterior probability and said assigned confidence grades for each of said classes; whereby said document is classified into one of said classes using said confidence grades.