Method and system for constructing a classifier

A computer hardware system for constructing a classifier classifying data records into specific categories, comprising:

• at least one processor, wherein the at least one processor configured to perform:
• clustering a set of records that are to be classified into a plurality of clusters of records by applying a clustering process to the set of records that are to be classified;
• creating a first classifier based upon the clustered set of records that are to be classified, the first classifier enabled to classify records into a plurality of training clusters;
• applying the first classifier to a set of training records to create a plurality of training clusters, each record in each training cluster of the plurality of training clusters having a corresponding predicted class;
• creating separate classifiers for each training cluster the plurality of training clusters;
• and,
• applying one of the created separate classifiers to a corresponding one of the clusters of records amongst the clustered set of records in order to classify the corresponding one of the clusters of records, and
• wherein the at least one processor first processes the set of records that are to be classified to determine a context before using the set of training records to classify the set of records based upon the determined context.

A non-transitory computer readable storage medium for constructing a classifier, comprising computer readable instructions, which, when executed on a computer system, cause the computer system to perform the steps of:

• a) clustering a set of records that are to be classified into a plurality of clusters of records by applying a clustering process to the set of records that are to be classified;
• b) creating a first classifier based upon the clustered set of records that are to be classified, the first classifier enabled to classify records into a plurality of training clusters;
• c) applying the first classifier to a set of training records to create a plurality of training clusters, each record in each training cluster of the plurality of training clusters having a corresponding predicted class;
• d) creating separate classifiers for each training cluster of the plurality of training clusters;
• and,
• e) applying one of the created separate classifiers to a corresponding one of the clusters of records amongst the clustered set of records in order to classify the corresponding one of the clusters of records, wherein the first classifier and also each separate classifier learns one or more sets of relationships that define each of a known set of predicted classes and wherein the computer system first processes the set of records that are to be classified to determine a context before using the set of training records to classify the set of records based upon the determined context.