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Loading... Kernels For Structured Data (Series in Machine Perception & Art Intelligence)by Thomas Gärtner
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This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by No library descriptions found. |
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Google Books — Loading... GenresMelvil Decimal System (DDC)006.31Information Computer Science; Knowledge and Systems Special Topics Artificial Intelligence Machine LearningLC ClassificationRatingAverage: No ratings.Is this you?Become a LibraryThing Author. |