Unsupervised Learning Algorithms

Β·
Β· Springer
ЭлСктронная ΠΊΠ½ΠΈΠ³Π°
558
ΠšΠΎΠ»ΠΈΡ‡Π΅ΡΡ‚Π²ΠΎ страниц
ΠžΡ†Π΅Π½ΠΊΠΈ ΠΈ ΠΎΡ‚Π·Ρ‹Π²Ρ‹ Π½Π΅ ΠΏΡ€ΠΎΠ²Π΅Ρ€Π΅Π½Ρ‹. ΠŸΠΎΠ΄Ρ€ΠΎΠ±Π½Π΅Π΅β€¦

Об элСктронной ΠΊΠ½ΠΈΠ³Π΅

This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners. The authors outline how these algorithms have found numerous applications including pattern recognition, market basket analysis, web mining, social network analysis, information retrieval, recommender systems, market research, intrusion detection, and fraud detection. They present how the difficulty of developing theoretically sound approaches that are amenable to objective evaluation have resulted in the proposal of numerous unsupervised learning algorithms over the past half-century. The intended audience includes researchers and practitioners who are increasingly using unsupervised learning algorithms to analyze their data. Topics of interest includeanomaly detection, clustering, feature extraction, and applications of unsupervised learning. Each chapter is contributed by a leading expert in the field.

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Π§Ρ‚ΠΎΠ±Ρ‹ ΠΎΡ‚ΠΊΡ€Ρ‹Ρ‚ΡŒ ΠΊΠ½ΠΈΠ³Ρƒ Π½Π° Ρ‚Π°ΠΊΠΎΠΌ устройствС для чтСния, ΠΊΠ°ΠΊ Kobo, скачайтС Ρ„Π°ΠΉΠ» ΠΈ Π΄ΠΎΠ±Π°Π²ΡŒΡ‚Π΅ Π΅Π³ΠΎ Π½Π° устройство. ΠŸΠΎΠ΄Ρ€ΠΎΠ±Π½Ρ‹Π΅ инструкции ΠΌΠΎΠΆΠ½ΠΎ Π½Π°ΠΉΡ‚ΠΈ Π² Π‘ΠΏΡ€Π°Π²ΠΎΡ‡Π½ΠΎΠΌ Ρ†Π΅Π½Ρ‚Ρ€Π΅.

Π”Ρ€ΡƒΠ³ΠΈΠ΅ ΠΊΠ½ΠΈΠ³ΠΈ Π°Π²Ρ‚ΠΎΡ€Π° M. Emre Celebi

ΠŸΠΎΡ…ΠΎΠΆΠΈΠ΅ элСктронныС ΠΊΠ½ΠΈΠ³ΠΈ