Abstract: The present invention provides an efficient method and system for performing data mining on large amounts of data using a multi-threaded Bayesian algorithm. The method for data mining includes receiving data from a database, performing multi-threaded classification on the data using a Naïve Bayes model and performing multi-threaded regression on the data based on a Naïve Bayes model. One of the multi threaded classification and regression steps may include processing the data according to a batch learning system, processing the data according to an incremental learning system, processing the data according to an online learning system, and processing the data according to a distributed learning system. One of the the multi-threaded classification and regression steps may include developing a set of rules from a set of training data. One of the multi-threaded classification and regression steps may comprise arranging the data into a plurality of groups.

Abstract: The notion of checkpointing model building is introduced to safeguard against the loss of computational results due to abnormal termination of long running computation algorithms. A checkpoint manager initiates a checkpoint, wherein initiation occurs by various scenarios, including dynamically, automatically and manually. A computation module executes the checkpoint on an in progress data computation. The checkpoint manager also monitors the execution of the checkpoint for abnormal termination. Upon a determination of abnormal checkpoint termination, the inability to resume model building from a checkpoint, the checkpoint manger either resumes model build from the checkpoint or aborts the model build.

Abstract: The present invention relates to progress notification systems, computer program products and methods of operation thereof, that reports processing progress of data mining operations at regular periodic intervals. The system comprises: an input/output interface for exchanging information with a network; a memory for storing updated progress objects associated with the data mining operation as a set of data mining algorithms progress in processing; and a processor coupled to the input/output interface and the memory, the processor for performing the data mining operation, the data mining operation implementing the set of data mining algorithms; and generating a notification object for the data mining operation at a pre-determined interval, the notification object based on the progress objects at each of the pre-determined intervals.

Abstract: A method, system, and computer program product for generating a representation of a data mining model that improves the transparency of data mining models so as to be more easily interpretable by human users. The method comprises the steps of: receiving a dataset, generating a callable version of the data mining model, and generating a tree representing decisional logic of the data mining model using the dataset.