World Scientific
Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×
Our website is made possible by displaying certain online content using javascript.
In order to view the full content, please disable your ad blocker or whitelist our website www.worldscientific.com.

System Upgrade on Fri, Jun 26th, 2020 at 5pm (ET)

During this period, our website will be offline for less than an hour but the E-commerce and registration of new users may not be available for up to 4 hours.
For online purchase, please visit us again. Contact us at [email protected] for any enquiries.
Abstract:

Data mining applications are common for quantitative modelling management problems resolution. As their learning curve has been very much simplified, is no surprise that many users try to apply data mining methods to data bases in a non-planned way. In this chapter, the CRISP-DM process model methodology is presented with the intention of avoiding common traps in data mining applications utilization. The use of this methodology is exemplified with serveral cases of application developed by the authors.