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An Adaptive Local Linear Embedding Algorithm

Zhang Yu-lin

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Abstract

Locally Linear Embedding algorithm (LLE) for its low computational complexity and efficiency of dimensionality reduction applied to many problems,the new adaptive local linear embedding (ALLE) algorithm is non-linear dimensionality reduction of data,extracting high-dimensional essential characteristics of the data and maintain the global geometry of data features,compared to experimental results show that the algorithm results show that the ALLE data for the non-ideal results were better than the LLE dimensionality reduction algorithm.

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What this paper is about

Locally Linear Embedding algorithm (LLE) for its low computational complexity and efficiency of dimensionality reduction applied to many problems,the new adaptive local linear embedding (ALLE) algorithm is non-linear dimensionality reduction of data,extracting high-dimensional essential characteristics of the data and maintain the global geometry of data features,compared to experimental results show that the algorithm results show that the ALLE data for the non-ideal results were better than the LLE dimensionality reduction algorithm.

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Available abstract

Locally Linear Embedding algorithm (LLE) for its low computational complexity and efficiency of dimensionality reduction applied to many problems,the new adaptive local linear embedding (ALLE) algorithm is non-linear dimensionality reduction of data,extracting high-dimensional essential characteristics of the data and maintain the global geometry of data features,compared to experimental results show that the algorithm results show that the ALLE data for the non-ideal results were better than the LLE dimensionality reduction algorithm.

Key concepts: Dimensionality reduction, Computer science, Embedding, Reduction (mathematics), Algorithm, Curse of dimensionality, Computational complexity theory, Ideal (ethics)

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