Discovering Knowledge in Data by Daniel T Larose
The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before.
Daniel T. Larose earned his PhD in Statistics at the University of Connecticut. He is Professor of Mathematical Sciences and Director of the Data Mining programs at Central Connecticut State University. His consulting clients have included Microsoft, Forbes Magazine, the CIT Group, KPMG International, Computer Associates, and Deloitte, Inc. This is Larose’s fourth book for Wiley.
Chantal D. Larose is an Assistant Professor of Statistics & Data Science at Eastern Connecticut State University (ECSU). She has co-authored three books on data science and predictive analytics. She helped develop data science programs at ECSU and at SUNY New Paltz. She received her PhD in Statistics from the University of Connecticut, Storrs in 2015 (dissertation title: Model-based Clustering of Incomplete Data).
| SKU | Unavailable |
| ISBN 13 | 9780470908747 |
| ISBN 10 | 0470908742 |
| Title | Discovering Knowledge in Data |
| Author | Daniel T Larose |
| Series | Wiley Series On Methods And Applications In Data Mining |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Wiley |
| Year published | 2014-07-11 |
| Number of pages | 336 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |