An Adaptive Local Linear Embedding Algorithm
Zhang Yu-lin
Abstract
Zhang Yu-lin
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.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
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)