Unsupervised learning approaches for dimensionality reduction and data visualization
Auteur :
Tripathy, B.K. / Sundareswaran, Anveshrithaa / Ghela, Shrusti
Éditeur :
Taylor & Francis Ltd
ISBN :
9781032041032
Date de publication :
25 sept. 2023
Dimensions :
23,4 x 15,6 cm
Poids :
453 g
Langue :
Anglais
Pays d'origine :
Grande Bretagne
This book describes algorithms like Locally Linear Embedding, Laplacian eigenmaps, Semidefinite Embedding, t-SNE to resolve the problem of dimensionality reduction in case of non-linear relationships within the data. Underlying mathematical concepts, derivations, proofs, strengths and limitations of these algorithms are discussed as well.