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  • Sách tham khảo
  • Ký hiệu PL/XG: 006.31 T815
    Nhan đề: The elements of statistical learning :
ISBN 9780387848570
DDC 006.31
Tác giả CN Hastie, Trevor
Nhan đề The elements of statistical learning : data mining, inference, and prediction / Trevor Hastie, Robert Tibshirani, J H Friedman
Lần xuất bản 2
Thông tin xuất bản New York : Springer, 2009
Mô tả vật lý 745 p.
Phụ chú Springer series in statistics.
Tóm tắt "During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics."
Từ khóa tự do Statistics.
Từ khóa tự do Electronic data processing.
Từ khóa tự do Supervised learning (Machine learning)
Khoa Khoa Cơ khí - Điện - Điện tử - Ô tô
Tác giả(bs) CN Friedman, J H
Tác giả(bs) CN Tibshiran, Robert
Địa chỉ Thư Viện Đại học Nguyễn Tất Thành
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100 |aHastie, Trevor
245 |aThe elements of statistical learning : |bdata mining, inference, and prediction / |cTrevor Hastie, Robert Tibshirani, J H Friedman
250 |a2
260 |aNew York : |bSpringer, |c2009
300 |a745 p.
500 |a Springer series in statistics.
520 |a "During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics."
541|aSpringer
653 |aStatistics.
653 |aElectronic data processing.
653 |aSupervised learning (Machine learning)
690 |aKhoa Cơ khí - Điện - Điện tử - Ô tô
700 |aFriedman, J H
700 |aTibshiran, Robert
852 |aThư Viện Đại học Nguyễn Tất Thành
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