| 摘要 |
A method, apparatus, and article of manufacture for performing data mining applications in a relational database management system. At least one analytic algorithm for enhanced back-propagation neural network processing is performed by a computer, wherein the analytic algorithm for enhanced back-propagation neural network processing includes SQL statements performed by the relational database management system directly against the relational database and programmatic iteration. The analytic algorithm for enhanced back-propagation neural network processing operates on data in the relational database that has been partitioned into training, testing and validation data sets. The analytic algorithm for enhanced back-propagation neural network processing maps the data in the training data sets to nodes in the neural network wherein the data is processed as it moves from an input node of the neural network through a hidden node of the neural network to an output node of the neural network. In addition, the analytic algorithm for enhanced back-propagation neural network processing determines an error difference between the output node's value and a target value as the data is mapped to the output node in the neural network, and changes a weight value for one or more of the nodes based on an accumulation of the error difference for the node, in order to get the neural network to converge on a solution. Finally, the analytic algorithm for enhanced back-propagation neural network processing cross-validates the changed weight value to prevent overfitting the node.
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