Using data mining to detect fraud
- Year
- 2000
- Tongue
- English
- Leaves
- 14
- Category
- Library
No coin nor oath required. For personal study only.
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If you have an abundance of data, but no idea what to do with it, this book was written for you! Packed with examples from an array of industries, Introduction to Data Mining Using SAS Enterprise Miner provides you with excellent starting points and practical guidelines to begin data mining today. A
<span><span><p><b>Detect fraud earlier to mitigate loss and prevent cascading damage</b></p><p><em>Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques</em> is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a k
Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementat
<b>Detect fraud earlier to mitigate loss and prevent cascading damage</b> <p><i>Fraud Analytics Using Descriptive, Predictive, and Social Network TechniquesΒ </i>is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigat
<b>The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner. <p>The Sample, Explore, Modify, Model, and Assess (SEMMA) methodology of SAS Enterprise Miner is an extremely valuable analytical tool for making critical business and marketing decisions. Until no