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Machine Learning And Data Mining In Pattern Recognition
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Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2018-07-09 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2013-07-11 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2013, held in New York, USA in July 2013. The 51 revised full papers presented were carefully reviewed and selected from 212 submissions. The papers cover the topics ranging from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2018-07-09 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer Science & Business Media. This book was released on 2011-08-12 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2011, held in New York, NY, USA. The 44 revised full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on classification and decision theory, theory of learning, clustering, application in medicine, webmining and information mining; and machine learning and image mining.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2011-08-12 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2011, held in New York, NY, USA. The 44 revised full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on classification and decision theory, theory of learning, clustering, application in medicine, webmining and information mining; and machine learning and image mining.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2017-07-01 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2017, held in New York, NY, USA in July/August 2017.The 31 full papers presented in this book were carefully reviewed and selected from 150 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.
Book Synopsis Data Mining and Machine Learning by : Mohammed J. Zaki
Download or read book Data Mining and Machine Learning written by Mohammed J. Zaki and published by Cambridge University Press. This book was released on 2020-01-30 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by :
Download or read book Machine Learning and Data Mining in Pattern Recognition written by and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2003-05-15 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning and Data Mining in Pattern Recognition, MLDM 2001, held in Leipzig, Germany in July 2001. The 26 revised full papers presented together with two invited papers were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections on case-based reasoning and associative memory; rule induction and grammars; clustering and conceptual clustering; data mining on signals, images, and spatio-temporal data; nonlinear function learning and neural net based learning; learning for handwriting recognition; statistical and evolutionary learning; and content-based image retrieval.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2012-07-02 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference, MLDM 2012, held in Berlin, Germany in July 2012. The 51 revised full papers presented were carefully reviewed and selected from 212 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2016-06-27 with total page 807 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2016, held in New York, NY, USA in July 2016. The 58 regular papers presented in this book were carefully reviewed and selected from 169 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer Science & Business Media. This book was released on 2007-07-16 with total page 927 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ever wondered what the state of the art is in machine learning and data mining? Well, now you can find out. This book constitutes the refereed proceedings of the 5th International Conference on Machine Learning and Data Mining in Pattern Recognition, held in Leipzig, Germany, in July 2007. The 66 revised full papers presented together with 1 invited talk were carefully reviewed and selected from more than 250 submissions. The papers are organized in topical sections.
Book Synopsis Pattern Recognition Algorithms for Data Mining by : Sankar K. Pal
Download or read book Pattern Recognition Algorithms for Data Mining written by Sankar K. Pal and published by CRC Press. This book was released on 2004-05-27 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks. Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer Science & Business Media. This book was released on 2005-07-08 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: We met again in front of the statue of Gottfried Wilhelm von Leibniz in the city of Leipzig. Leibniz, a famous son of Leipzig, planned automatic logical inference using symbolic computation, aimed to collate all human knowledge. Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled “machine learning” and “data mining”, whose topics are text mining, knowledge discovery, and applications. This meeting from the first focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the viewpoints of machine learning and data mining. Though it was a challenging program in the late 1990s, the idea has inspired new starting points in pattern recognition and effects in other areas such as cognitive computer vision.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2015-06-30 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2015, held in Hamburg, Germany in July 2015. The 41 full papers presented were carefully reviewed and selected from 123 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2014-07-17 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2003-06-26 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of machine learning and data mining in connection with pattern recognition enjoys growing popularity and attracts many researchers. Automatic pattern recognition systems have proven successful in many applications. The wide use of these systems depends on their ability to adapt to changing environmental conditions and to deal with new objects. This requires learning capabilities on the parts of these systems. The exceptional attraction of learning in pattern recognition lies in the specific data themselves and the different stages at which they get processed in a pattern recognition system. This results a specific branch within the field of machine learning. At the workshop, were presented machine learning approaches for image pre-processing, image segmentation, recognition and interpretation. Machine learning systems were shown on applications such as document analysis and medical image analysis. Many databases are developed that contain multimedia sources such as images, measurement protocols, and text documents. Such systems should be able to retrieve these sources by content. That requires specific retrieval and indexing strategies for images and signals. Higher quality database contents can be achieved if it were possible to mine these databases for their underlying information. Such mining techniques have to consider the specific characteristic of the image sources. The field of mining multimedia databases is just starting out. We hope that our workshop can attract many other researchers to this subject.
