Customer relationship management (CRM) is an important element in all forms of industry. This process involves ensuring that the customers a business are satisfied with product or services they paying for. Since most businesses collect and store large volumes data about their customers; it easy for analysts to use perform predictive analysis. One aspect this includes customer retention churn. c...

Existing algorithms for learning optimal decision trees can be put into two categories: based on the use of Mixed Integer Programming (MIP) solvers and dynamic programming (DP) itemsets. While DP are fastest, their main disadvantage compared to MIP-based approaches is that amount memory these may require find an solution not bounded. Consequently, some datasets only executed machines with large...

The paper proposes a method for efficiently store collections of multi-purpose decision trees within a native distributed XML database. The predictive information for building the XML decision trees is gathered through Web mining techniques and methodologies. In order to share data from heterogeneous sources, the model employs semantic Web languages to describe and represent data sources. The u...

Decision trees are one of the most popular methods of data mining. Decision trees partition large amounts of data into smaller segments by applying a series of rules. Creating and evaluating decision trees benefits greatly from visualization of the trees and diagnostic measures of their effectiveness. This paper describes an application, EMTree Results Viewer, that supports decision tree analys...

Recent work has shown that the use of finite-state transducers (FST’s) has many advantages in large vocabulary speech recognition. Most past work has focused on the use of triphone phonetic decision trees. However, numerous applications use decision trees that condition on wider contexts; for example, many systems at IBM use 11-phone phonetic decision trees. Alas, large-context phonetic decisio...