Data Analysis in Bi-partial Perspective: Clustering and Beyond 1st ed. 2020 [Kõva köide]

  • Formaat: Hardback, 153 pages, kõrgus x laius: 235x155 mm, kaal: 432 g, XIX, 153 p., 1 Hardback
  • Sari: Studies in Computational Intelligence 818
  • Ilmumisaeg: 02-Apr-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030133885
  • ISBN-13: 9783030133887
Teised raamatud teemal:
  • Kõva köide
  • Hind: 99,44 EUR*
  • Tavahind: 132,59 EUR
  • Säästad 25%
  • Lisa soovinimekirja
  • Lisa ostukorvi
  • Kogus:
  • Tasuta tarne
  • Tellimisaeg 2-4 nädalat
  • Raamatut on võimalik tellida. Raamatu kohalejõudmiseks kirjastusest kulub orienteeruvalt 2-4 nädalat.
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Formaat: Hardback, 153 pages, kõrgus x laius: 235x155 mm, kaal: 432 g, XIX, 153 p., 1 Hardback
  • Sari: Studies in Computational Intelligence 818
  • Ilmumisaeg: 02-Apr-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030133885
  • ISBN-13: 9783030133887
Teised raamatud teemal:

This book presents the bi-partial approach to data analysis, which is both uniquely general and enables the development of techniques for many data analysis problems, including related models and algorithms. It is based on adequate representation of the essential clustering problem: to group together the similar, and to separate the dissimilar. This leads to a general objective function and subsequently to a broad class of concrete implementations. Using this basis, a suboptimising procedure can be developed, together with a variety of implementations.

This procedure has a striking affinity with the classical hierarchical merger algorithms, while also incorporating the stopping rule, based on the objective function. The approach resolves the cluster number issue, as the solutions obtained include both the content and the number of clusters. Further, it is demonstrated how the bi-partial principle can be effectively applied to a wide variety of problems in data analysis.

The book offers a valuable resource for all data scientists who wish to broaden their perspective on basic approaches and essential problems, and to thus find answers to questions that are often overlooked or have yet to be solved convincingly. It is also intended for graduate students in the computer and data sciences, and will complement their knowledge and skills with fresh insights on problems that are otherwise treated in the standard “academic” manner.

Preface.
Chapter
1. Notation and main assumptions.
Chapter
2. The problem of cluster analysis.
Chapter
3. The general formulation of the objective function.
Chapter
4. Formulations and rationales for other problems in data analysis, etc.

Tellige see raamat tutvumiseks meie kauplusesse!Raekoja plats 11, 51004 Tartu

Juhul, kui soovite raamatuga enne ostu tutvuda, siis palun sisestaga allpool oma nimi ning e-mail.
Võimaluse korral tellime raamatu poodi ning teavitame ka teid, kui raamat on müügile jõudnud.

* - väljad on kohustuslikud