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Nonlinear Dimensionality Reduction
ISBN: 9781441922885 / Angielski / Miękka / 2010 / 309 str. Termin realizacji zamówienia: ok. 20 dni roboczych. Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets. Traditional methods like principal component analysis and classical metric multidimensional scaling suffer from being based on linear models. Until recently, very few methods were able to reduce the data dimensionality in a nonlinear way. However, since the late nineties, many new methods have been developed and nonlinear dimensionality reduction, also called manifold learning, has become a hot topic. New advances that account for this rapid growth are, e.g. the use of graphs... Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets. Traditional methods like principa... |
cena:
549,74 zł |
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Nonlinear Dimensionality Reduction
ISBN: 9780387393506 / Angielski / Twarda / 2007 / 308 str. Termin realizacji zamówienia: ok. 20 dni roboczych. Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets. Traditional methods like principal component analysis and classical metric multidimensional scaling suffer from being based on linear models. Until recently, very few methods were able to reduce the data dimensionality in a nonlinear way. However, since the late nineties, many new methods have been developed and nonlinear dimensionality reduction, also called manifold learning, has become a hot topic. New advances that account for this rapid growth are, e.g. the use of graphs... Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets. Traditional methods like principa... |
cena:
549,74 zł |
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Similarity-Based Clustering: Recent Developments and Biomedical Applications
ISBN: 9783642018046 / Angielski / Miękka / 2009 / 203 str. Termin realizacji zamówienia: ok. 20 dni roboczych. Similarity-based learning methods have a great potential as an intuitive and ?exible toolbox for mining, visualization, and inspection of largedata sets. They combine simple and human-understandable principles, such as distance-based classi?cation, prototypes, or Hebbian learning, with a large variety of di?erent, problem-adapted design choices, such as a data-optimum topology, similarity measure, or learning mode. In medicine, biology, and medical bioinformatics, more and more data arise from clinical measurements such as EEG or fMRI studies for monitoring brain activity, mass spectrometry...
Similarity-based learning methods have a great potential as an intuitive and ?exible toolbox for mining, visualization, and inspection of largedata se...
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cena:
196,31 zł |
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