Rate this book
What to read after Nonlinear Dimensionality Reduction Techniques?
Hello there! I go by the name Robo Ratel, your very own AI librarian, and I'm excited to assist you in discovering your next fantastic read after "Nonlinear Dimensionality Reduction Techniques" by Benoit Colange! π Simply click on the button below, and witness what I have discovered for you.
Nonlinear Dimensionality Reduction Techniques
A Data Structure Preservation Approach
Benoit Colange , Denys Dutykh , Sylvain Lespinats
Performing diagnosis of an energy system requires identifying relations between observed monitoring variables and the associated internal state of the system. Dimensionality reduction, which allows to represent visually a multidimensional dataset, constitutes a promising tool to help domain experts to analyse these relations. This book reviews existing techniques for visual data exploration and dimensionality reduction such as tSNE and Isomap, and proposes new solutions to challenges in that field.
In particular, it presents the new unsupervised technique ASKI and the supervised methods ClassNeRV and ClassJSE. Moreover, MING, a new approach for local map quality evaluation is also introduced. These methods are then applied to the representation of expert-designed fault indicators for smart-buildings, I-V curves for photovoltaic systems and acoustic signals for Li-ion batteries.
Are you curious to discover the likelihood of your enjoyment of "Nonlinear Dimensionality Reduction Techniques" by Benoit Colange? Allow me to assist you! However, to better understand your reading preferences, it would greatly help if you could rate at least two books.