A data mining decision tree system that uncovers patterns, associations, anomalies, and other statistically significant structures in data by reading and displaying data files, extracting relevant features for each of the objects, and using a method of recognizing patterns among the objects based upon object features through a decision tree that reads the data, sorts the data if necessary, determines the best manner to split the data into subsets according to some criterion, and splits the data.

 
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< Maximizing mutual information between observations and hidden states to minimize classification errors

< Signal processing circuit involving local synchronous behavior

> Error analysis fed from a knowledge base

> Distributed OLAP-based association rule generation method and system

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