Statistical regression classification linear von matloff norman (9 Ergebnisse)

Paperback. Zustand: Fair. This text provides a modern introduction to regression and classification with an emphasis on big data and R. Each chapter is partitioned into a main body section and an extras section. The main body uses math stat very sparingly and always in the context of something concrete, which means that readers can skip the math stat content entirely if they wish. The extras section is for those who feel comfortable with analysis using math stat.…

Paperback. Zustand: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Zustand: Good. 1st Edition. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: New.

Paperback. Zustand: Brand New. 489 pages. 9.00x6.00x1.00 inches. In Stock.

Taschenbuch. Zustand: Neu. Neuware - This text provides a modern introduction to regression and classification with an emphasis on big data and R. Each chapter is partitioned into a main body section and an extras section. The main body uses math stat very sparingly and always in the context of something concrete, which means that readers can skip the math stat content entirely if they wish. The extras section is for those who feel comfortable with analysis using math stat.…

Zustand: New.

Zustand: New. Norman Matloff is a professor of computer science at the University of California, Davis, and was a founder of the Statistics Department at that institution. Statistical Regression and Classification: From Linear Models to Machin.

Buch. Zustand: Neu. Neuware - This text provides a modern introduction to regression and classification with an emphasis on big data and R. Each chapter is partitioned into a main body section and an extras section. The main body uses math stat very sparingly and always in the context of something concrete, which means that readers can skip the math stat content entirely if they wish. The extras section is for those who feel comfortable with analysis using math stat.…