1. A computer implemented method for detecting spam messages, comprising: determining a first stage probability of whether a received message is a spam message, wherein the first stage probability is determined by evaluating the received message in relation to a subset of test messages, wherein each subset test message in the subset of test messages was previously identified as either valid or spam; receiving an indication that a first stage classifier is unsure, based on the first stage probability, as to whether the received message is a spam message; determining that the first stage probability is greater than a lower limit for combining probabilities and is less than an upper limit for combining probabilities, wherein the lower limit for combining probabilities indicates a probability value below which the first stage probability will not be combined with a second stage probability to determine whether the received message is a spam message, and wherein the upper limit for combining probabilities indicates a probability value above which the received message is marked as a spam message without combining the first stage probability with the second stage probability and wherein the determining the lower limit is determined by: setting the lower limit to an initial value; counting correctly identified spam messages from a randomized test set of messages; counting correctly identified valid messages from the randomized test set of messages; counting incorrectly identified spam messages from the randomized test set of messages; counting incorrectly identified valid messages from the randomized test set of messages; calculating, for each of multiple incremental values of the lower limit, a lower limit classification ratio as a ratio of: a first sum of: the count of the correctly identified spam messages; and the count of the correctly identified valid messages; over a second sum of: the count of the incorrectly identified spam messages; the count of the incorrectly identified valid messages; and one; and selecting the incremental value of the lower limit that corresponds to the highest value of the lower limit classification ratio; determining a second stage probability of whether the received message is a spam message, wherein the second stage probability is determined by evaluating the received message in relation to a subset-specific master set of test messages, which includes the subset of test messages, wherein each subset-specific master set test message in the subset-specific master set of test messages was previously identified as either valid or spam; computing a combined probability based on the first stage probability and the second stage probability; determining that the combined probability is greater than a threshold probability at which a threshold classification ratio is highest, wherein the classification ratio comprises a ratio of correctly identified spam messages over incorrectly identified spam messages.