Dimensionality Reduction with Unsupervised Nearest Neighbors
Oliver Kramer
mai 2013 · Intelligent Systems Reference Library 51. raamat · Springer Science & Business Media
E-raamat
132
lehekülge
reportHinnangud ja arvustused pole kinnitatud. Lisateave
Teave selle e-raamatu kohta
This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with independent parameterizations. Extensions that allow the embedding of incomplete and noisy patterns are introduced. Various optimization approaches are compared, from evolutionary to swarm-based heuristics. Experimental comparisons to related methodologies taking into account artificial test data sets and also real-world data demonstrate the behavior of UNN in practical scenarios. The book contains numerous color figures to illustrate the introduced concepts and to highlight the experimental results.
Hinnake seda e-raamatut
Andke meile teada, mida te arvate.
Lugemisteave
Nutitelefonid ja tahvelarvutid
Installige rakendus Google Play raamatud Androidile ja iPadile/iPhone'ile. See sünkroonitakse automaatselt teie kontoga ja see võimaldab teil asukohast olenemata lugeda nii võrgus kui ka võrguühenduseta.
Sülearvutid ja arvutid
Google Playst ostetud audioraamatuid saab kuulata arvuti veebibrauseris.
E-lugerid ja muud seadmed
E-tindi seadmetes (nt Kobo e-lugerid) lugemiseks peate faili alla laadima ja selle oma seadmesse üle kandma. Failide toetatud e-lugeritesse teisaldamiseks järgige üksikasjalikke abikeskuse juhiseid.
