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Data mining with R

Learning with case studies

Autori

  • Kolektív autorov

Hodnotenie knihy

Parametre

  • 305 stránok
  • 11 hodin čítania

Viac o knihe

The versatile capabilities and large set of add-on packages make R an excellent alternative to many existing and often expensive data mining tools. Exploring this area from the perspective of a practitioner, Data Mining with Learning with Case Studies uses practical examples to illustrate the power of R and data mining. Assuming no prior knowledge of R or data mining/statistical techniques, the book covers a diverse set of problems that pose different challenges in terms of size, type of data, goals of analysis, and analytical tools. To present the main data mining processes and techniques, the author takes a hands-on approach that utilizes a series of detailed, real-world case With these case studies, the author supplies all necessary steps, code, and data. Web ResourceA supporting website mirrors the do-it-yourself approach of the text. It offers a collection of freely available R source files that encompass all the code used in the case studies. The site also provides the data sets from the case studies as well as an R package of several functions.

Nákup knihy

Data mining with R, Kolektív autorov

Jazyk
Rok vydania
2011
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Platobné metódy

3,8
Veľmi dobrá
76 Hodnotenie

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Titul
Data mining with R
Podtitul
Learning with case studies
Jazyk
anglicky
Vydavateľ
CRC Press
Rok vydania
2011
Väzba
pevná
Počet strán
305
ISBN10
1439810184
ISBN13
9781439810187
Série
Hodnotenie
3,8 z 5
Anotácia
The versatile capabilities and large set of add-on packages make R an excellent alternative to many existing and often expensive data mining tools. Exploring this area from the perspective of a practitioner, Data Mining with Learning with Case Studies uses practical examples to illustrate the power of R and data mining. Assuming no prior knowledge of R or data mining/statistical techniques, the book covers a diverse set of problems that pose different challenges in terms of size, type of data, goals of analysis, and analytical tools. To present the main data mining processes and techniques, the author takes a hands-on approach that utilizes a series of detailed, real-world case With these case studies, the author supplies all necessary steps, code, and data. Web ResourceA supporting website mirrors the do-it-yourself approach of the text. It offers a collection of freely available R source files that encompass all the code used in the case studies. The site also provides the data sets from the case studies as well as an R package of several functions.