Introduction To Business Data Mining
Olson, David L.; Shi, Yong
Verkauft von ICTBooks, Wichita, KS, USA
AbeBooks-Verkäufer seit 15. Mai 2023
Gebraucht - Hardcover
Zustand: Gebraucht - Befriedigend
Anzahl: 1 verfügbar
In den Warenkorb legenVerkauft von ICTBooks, Wichita, KS, USA
AbeBooks-Verkäufer seit 15. Mai 2023
Zustand: Gebraucht - Befriedigend
Anzahl: 1 verfügbar
In den Warenkorb legenBook shows wear from use but remains a usable copy. May include writing highlighting underlining library markings. LISTING USES STOCK PHOTOS AND COVER MAY VARY.Ships via USPS and typically arrives within 10-12 business days.
Bestandsnummer des Verkäufers ICV.0072959711.G
Introduction to Business Data Mining was developed to introduce students, as opposed to professional practitioners or engineering students, to the fundamental concepts of data mining. Most importantly, this text shows readers how to gather and analyze large sets of data to gain useful business understanding.
A four part organization introduces the material (Part I), describes and demonstrated basic data mining algorithms (Part II), focuses on the business applications of data mining (Part III), and presents an overview of the developing areas in this field, including web mining, text mining, and the ethical aspects of data mining. (Part IV).
The author team has had extensive experience with the quantitative analysis of business as well as with data mining analysis. They have both taught this material and used their own graduate students to prepare the text’s data mining reports. Using real-world vignettes and their extensive knowledge of this new subject, David Olson and Yong Shi have created a text that demonstrates data mining processes and techniques needed for business applications.
Introduction to Business Data Mining was developed to introduce students, as opposed to professional practitioners or engineering students, to the fundamental concepts of data mining. Most importantly, this text shows readers how to gather and analyze large sets of data to gain useful business understanding.
A four part organization introduces the material (Part I), describes and demonstrated basic data mining algorithms (Part II), focuses on the business applications of data mining (Part III), and presents an overview of the developing areas in this field, including web mining, text mining, and the ethical aspects of data mining. (Part IV).
The author team has had extensive experience with the quantitative analysis of business as well as with data mining analysis. They have both taught this material and used their own graduate students to prepare the text’s data mining reports. Using real-world vignettes and their extensive knowledge of this new subject, David Olson and Yong Shi have created a text that demonstrates data mining processes and techniques needed for business applications.
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