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Author: Oliver Kramer
Publisher: Springer Science & Business Media
ISBN: 3642386520
Category : Technology & Engineering
Languages : en
Pages : 137
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Book Description
This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with independent parameterizations. Extensions that allow the embedding of incomplete and noisy patterns are introduced. Various optimization approaches are compared, from evolutionary to swarm-based heuristics. Experimental comparisons to related methodologies taking into account artificial test data sets and also real-world data demonstrate the behavior of UNN in practical scenarios. The book contains numerous color figures to illustrate the introduced concepts and to highlight the experimental results.
Author: Oliver Kramer
Publisher: Springer Science & Business Media
ISBN: 3642386520
Category : Technology & Engineering
Languages : en
Pages : 137
Get Book Here
Book Description
This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with independent parameterizations. Extensions that allow the embedding of incomplete and noisy patterns are introduced. Various optimization approaches are compared, from evolutionary to swarm-based heuristics. Experimental comparisons to related methodologies taking into account artificial test data sets and also real-world data demonstrate the behavior of UNN in practical scenarios. The book contains numerous color figures to illustrate the introduced concepts and to highlight the experimental results.
Author: Joaquim Filipe
Publisher: Springer
ISBN: 3642369073
Category : Computers
Languages : en
Pages : 458
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Book Description
This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Conference on Agents and Artificial Intelligence, ICAART 2012, held in Vilamoura, Portugal, in February 2012. The 28 revised full papers presented together with one invited paper were carefully reviewed and selected from 292 submissions. The papers are organized in two topical sections on artificial intelligence and on agents.
Author: Michel Verleysen
Publisher: Presses universitaires de Louvain
ISBN: 2875870157
Category :
Languages : en
Pages : 615
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Book Description
Author: Gabriele Kern-Isberner
Publisher: Springer
ISBN: 3319671901
Category : Computers
Languages : en
Pages : 411
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Book Description
This book constitutes the refereed proceedings of the 40th Annual German Conference on Artificial Intelligence, KI 2017 held in Dortmund, Germany in September 2017. The 20 revised full technical papers presented together with 16 short technical communications were carefully reviewed and selected from 73 submissions. The conference cover a range of topics from, e. g., agents, robotics, cognitive sciences, machine learning, planning, knowledge representation, reasoning, and ontologies, with numerous applications in areas like social media, psychology, transportation systems and reflecting the richness and diversity of their field.
Author: Maria J. Blesa
Publisher: Springer
ISBN: 3642385168
Category : Computers
Languages : en
Pages : 222
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Book Description
This book constitutes the refereed proceedings of the 8th International Workshop on Hybrid Metaheuristics, HM 2013, held in Ischia, Italy, in May 2013. The 16 revised full papers presented were carefully reviewed and selected from 30 submissions. The selected papers cover both theoretical and experimental results, including new paradigmatic hybrid solvers and automatic design approaches as well as applications to logistics and public transport.
Author: B.K. Tripathy
Publisher: CRC Press
ISBN: 1000438317
Category : Business & Economics
Languages : en
Pages : 174
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Book Description
Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization describes such algorithms as Locally Linear Embedding (LLE), Laplacian Eigenmaps, Isomap, Semidefinite Embedding, and t-SNE to resolve the problem of dimensionality reduction in the case of non-linear relationships within the data. Underlying mathematical concepts, derivations, and proofs with logical explanations for these algorithms are discussed, including strengths and limitations. The book highlights important use cases of these algorithms and provides examples along with visualizations. Comparative study of the algorithms is presented to give a clear idea on selecting the best suitable algorithm for a given dataset for efficient dimensionality reduction and data visualization. FEATURES Demonstrates how unsupervised learning approaches can be used for dimensionality reduction Neatly explains algorithms with a focus on the fundamentals and underlying mathematical concepts Describes the comparative study of the algorithms and discusses when and where each algorithm is best suitable for use Provides use cases, illustrative examples, and visualizations of each algorithm Helps visualize and create compact representations of high dimensional and intricate data for various real-world applications and data analysis This book is aimed at professionals, graduate students, and researchers in Computer Science and Engineering, Data Science, Machine Learning, Computer Vision, Data Mining, Deep Learning, Sensor Data Filtering, Feature Extraction for Control Systems, and Medical Instruments Input Extraction.
Author: Birte Glimm
Publisher: Springer
ISBN: 3642333478
Category : Computers
Languages : en
Pages : 278
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Book Description
This book constitutes the refereed proceedings of the 35th Annual German Conference on Artificial Intelligence, KI 2012, held in Saarbrücken, Germany, in September 2012. The 19 revised full papers presented together with 9 short papers were carefully reviewed and selected from 57 submissions. The papers contain research results on theory and applicaiton of all aspects of AI.
Author: Eklas Hossain
Publisher: Springer Nature
ISBN: 3031469909
Category : Computers
Languages : en
Pages : 465
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Book Description
Machine Learning Crash Course for Engineers is a reader-friendly introductory guide to machine learning algorithms and techniques for students, engineers, and other busy technical professionals. The book focuses on the application aspects of machine learning, progressing from the basics to advanced topics systematically from theory to applications and worked-out Python programming examples. It offers highly illustrated, step-by-step demonstrations that allow readers to implement machine learning models to solve real-world problems. This powerful tutorial is an excellent resource for those who need to acquire a solid foundational understanding of machine learning quickly.
Author: Oliver Kramer
Publisher: Springer
ISBN: 3319333836
Category : Technology & Engineering
Languages : en
Pages : 120
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Book Description
This book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strategies. The set of methods comprises covariance matrix estimation, meta-modeling of fitness and constraint functions, dimensionality reduction for search and visualization of high-dimensional optimization processes, and clustering-based niching. After giving an introduction to evolution strategies and machine learning, the book builds the bridge between both worlds with an algorithmic and experimental perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python using the machine learning library scikit-learn. The examples are conducted on typical benchmark problems illustrating algorithmic concepts and their experimental behavior. The book closes with a discussion of related lines of research.
Author: Raju Sarkar
Publisher: Springer Nature
ISBN: 981997707X
Category :
Languages : en
Pages : 328
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Book Description
