METHOD FOR FAST LARGE SCALE DATA MINING USING LOGISTIC REGRESSION

A classifier using a logistic regression technique permits previously acquired search results to be used to perform a new search. A user inputs search terms and queries a database of previous search results. A logistical regression calculation is performed using sets of data such that the time execution performance is at least a factor of 10 improvement over a conventional technique. In our experiments where real world data was used, the execution time was reduced up to 353 times as compared to the conventional technique. The Iteratively Reweighted Least Squares (IRLS) method is used for the logistical regression method and beta vector values are calculated from the database data set. A vector of the user input terms is multiplied by the beta vector values to produce an ordered list of documents satisfying the user search terms.