locally linear embedding | An Introduction to Locally Linear Embedding

Keyword	CPC	PCC	Volume	Score	Length of keyword
locally linear embedding	0.37	0.2	9322	66	24
locally	1.78	0.4	9690	41	7
linear	0.12	0.8	6180	74	6
embedding	1.05	0.1	2056	86	9

Keyword	CPC	PCC	Volume	Score
locally linear embedding	1.56	1	2405	3

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An Introduction to Locally Linear Embedding - New York …
nyu.edu

https://cs.nyu.edu/~roweis/lle/papers/lleintro.pdf

WEBHere we describe locally linear embedding (LLE), an unsu-pervised learning algorithm that computes low dimensional, neighborhood preserving embeddings of high dimensional data. LLE attempts to discover nonlinear structure in high dimensional data by exploiting the local symme-tries of linear reconstructions.

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2.2. Manifold learning — scikit-learn 1.4.2 documentation
scikit-learn.org

https://scikit-learn.org/stable/modules/manifold.html

WEBLocally Linear Embedding ¶. Locally linear embedding (LLE) seeks a lower-dimensional projection of the data which preserves distances within local neighborhoods. It can be thought of as a series of local Principal Component Analyses which are globally compared to find the best non-linear embedding.

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Nonlinear Dimensionality Reduction by Locally Linear Embedding
science.org

https://www.science.org/doi/10.1126/science.290.5500.2323

WEBDec 22, 2000 · Here, we introduce locally linear embedding (LLE), an unsupervised learning algorithm that computes low-dimensional, neighborhood-preserving embeddings of high-dimensional inputs. Unlike clustering methods for local dimensionality reduction, LLE maps its inputs into a single global coordinate system of lower dimensionality, and its ...

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Nonlinear Dimensionality Reduction I: Local Linear Embedding
cmu.edu

https://www.stat.cmu.edu/~cshalizi/350/lectures/14/lecture-14.pdf

WEBNonlinear Dimensionality Reduction I: Local Linear Embedding. 36-350, Data Mining. 5 October 2009. 1 Why We Need Nonlinear Dimensionality Re-duction. Consider the points shown in Figure 1. Even though there are two features, a.k.a. coordinates, all of the points fall on a one-dimensional curve (as it hap-pens, a logarithmic spiral).

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sklearn.manifold.locally_linear_embedding — scikit-learn 1.4.2
scikit-learn.org

https://scikit-learn.org/stable/modules/generated/sklearn.manifold.locally_linear_embedding.html

WEBsklearn.manifold.locally_linear_embedding(X, *, n_neighbors, n_components, reg=0.001, eigen_solver='auto', tol=1e-06, max_iter=100, method='standard', hessian_tol=0.0001, modified_tol=1e-12, random_state=None, n_jobs=None) [source] ¶. Perform a Locally Linear Embedding analysis on the data. Read more in the User Guide.

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Locally Linear Embedding in machine learning - GeeksforGeeks
geeksforgeeks.org

https://www.geeksforgeeks.org/locally-linear-embedding-in-machine-learning/

WEBOct 6, 2023 · Locally Linear Embedding (LLE) is a dimensionality reduction technique used in machine learning and data analysis. It focuses on preserving local relationships between data points when mapping high-dimensional data to a lower-dimensional space. Here, we will explain the LLE algorithm and its parameters.

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Locally Linear Embedding and its Variants: Tutorial and Survey
arxiv.org

https://arxiv.org/abs/2011.10925

WEBNov 22, 2020 · Locally Linear Embedding and its Variants: Tutorial and Survey. Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley. This is a tutorial and survey paper for Locally Linear Embedding (LLE) and its variants. The idea of LLE is fitting the local structure of manifold in the embedding space.

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Locally Linear Embedding and its Variants: Tutorial and Survey
arxiv.org

https://arxiv.org/pdf/2011.10925

WEBLocally Linear Embedding (LLE) (Roweis & Saul, 2000; Chen & Liu, 2011) is a nonlinear spectral dimensionality reduction method (Saul et al., 2006) which can be used for manifold embedding and feature extraction (Ghojogh et al., 2019e). LLE tries to preserve the local structure of data in the embedding space.

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Locally Linear Embedding | SpringerLink
springer.com

https://link.springer.com/chapter/10.1007/978-3-031-10602-6_8

WEBFeb 3, 2023 · Locally Linear Embedding. Benyamin Ghojogh, Mark Crowley, Fakhri Karray & Ali Ghodsi. Chapter. First Online: 03 February 2023. 1526 Accesses. Abstract. Locally Linear Embedding (LLE) is a nonlinear spectral dimensionality reduction method that can be used for manifold embedding and feature extraction. Download chapter PDF. …

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Locally Linear Embedding (LLE) Homepage - New York University
nyu.edu

https://cs.nyu.edu/~roweis/lle/

WEBLocally Linear Embedding (LLE) Homepage. Sam T. Roweis & Lawrence K. Saul. Jump to: A detailed tutorial description of the algorithm . References and links to LLE publications and (p)reprints. Gallery of example pictures and animations. LLE code page. Some notes and pointers to related work .

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