Data Analysis and Optimization: In Honor of Boris Mirkin's 80th Birthday
Goldengorin, Boris, Kuznetsov, Sergei
- 出版商: Springer
- 出版日期: 2024-09-25
- 售價: $7,030
- 貴賓價: 9.5 折 $6,679
- 語言: 英文
- 頁數: 422
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3031316568
- ISBN-13: 9783031316562
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相關分類:
Data Science
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相關主題
商品描述
This book presents the state-of-the-art in the emerging field of data science and includes models for layered security with applications in the protection of sites--such as large gathering places--through high-stake decision-making tasks. Such tasks include cancer diagnostics, self-driving cars, and others where wrong decisions can possibly have catastrophic consequences. Additionally, this book provides readers with automated methods to analyze patterns and models for various types of data, with applications ranging from scientific discovery to business intelligence and analytics.
The book primarily includes exploratory data analysis, pattern mining, clustering, and classification supported by real life case studies. The statistical section of this book explores the impact of data mining and modeling on the predictability assessment of time series. Further new notions of mean values based on ideas of multi-criteria optimization are compared with their conventional definitions, leading to new algorithmic approaches to the calculation of the suggested new means.The style of the written chapters and the provision of a broad yet in-depth overview of data mining, integrating novel concepts from machine learning and statistics, make the book accessible to upper level undergraduate and graduate students in data mining courses. Students and professionals specializing in computer and management science, data mining for high-dimensional data, complex graphs and networks will benefit from the cutting-edge ideas and practically motivated case studies in this book.
商品描述(中文翻譯)
本書介紹了數據科學這一新興領域的最新進展，並包含了分層安全模型，應用於保護大型聚集場所等地點，通過高風險決策任務進行保護。這些任務包括癌症診斷、自駕車等，錯誤的決策可能會導致災難性的後果。此外，本書還為讀者提供了自動化的方法來分析各類數據的模式和模型，應用範圍從科學發現到商業智慧和分析。
本書主要包括探索性數據分析、模式挖掘、聚類和分類，並以真實案例研究為支持。書中的統計部分探討了數據挖掘和建模對時間序列預測評估的影響。此外，基於多準則優化思想的新均值概念與其傳統定義進行比較，從而導致計算建議的新均值的新算法方法。
書中各章節的寫作風格以及對數據挖掘的廣泛而深入的概述，整合了來自機器學習和統計學的新概念，使本書對於高年級本科生和研究生的數據挖掘課程變得易於理解。專注於計算機與管理科學、高維數據的數據挖掘、複雜圖形和網絡的學生和專業人士，將從本書中的前沿思想和實際案例研究中受益。
作者簡介
Professor Sergei O. Kuznetsov graduated from the Faculty of Applied Mathematics and Control of the Moscow Institute for Physics and Technology in 1985. He obtained his Doctor of Science Degree in Theoretical Computer Science at the Computing Center of Russian Academy of Science. Since 2006 the Head of Department for Data Analysis and Artificial Intelligence, Head of the International Laboratory for Intelligent Systems and Structural Analysis and Academic Supervisor of the Data Science master program at National Research University Higher School of Economics (Moscow). His researchinterests are in the algorithms of data mining, knowledge discovery, and Formal Concept Analysis.
作者簡介(中文翻譯)
Boris Goldengorin 是數據修正和基於容忍度的算法的作者和發明者，這些算法應用於運籌學、供應鏈管理、定量物流、工業工程、數據和股市分析等多個問題。Boris 發表了超過 100 篇文章，這些文章刊登於多個國際知名期刊，包括《Journal of Algebraic Combinatorics》、《Discrete Optimization》、《Journal of Combinatorial Optimization》、《Journal of Global Optimization》、《Operations Research》、《Management Science》、《European Journal of Operational Research》、《Journal of Operational Research Society》、《Mathematical and Computer Modelling》、《Computers & Operations Research》、《Computers & Industrial Engineering》、《Expert Systems with Applications》、《Journal of Heuristics》、《Optimization Methods & Software》、《Computational Management Science》等等。Goldengorin 博士出版了四本專著、三本教科書，並擔任五本有關數學規劃、博弈論、組合優化、網絡分析算法、圖論和大數據分析的書籍的編輯。他是《Journal of Global Optimization》、《Journal of Combinatorial Optimization》、《SN Operations Research Forum》的副編輯，並且是烏克蘭國立塔拉斯·舍甫琴科大學《Journal of Computational and Applied Mathematics》編輯委員會的成員。
謝爾蓋·O·庫茲涅佐夫教授於 1985 年畢業於莫斯科物理技術學院應用數學與控制系。他在俄羅斯科學院計算中心獲得了理論計算機科學的博士學位。自 2006 年以來，他擔任國立研究大學高等經濟學院（莫斯科）數據分析與人工智慧系主任、智能系統與結構分析國際實驗室主任，以及數據科學碩士課程的學術主管。他的研究興趣包括數據挖掘、知識發現和形式概念分析的算法。
