...文 一步,对基于全局的等距映射方法(Isometric Feature Mapping, Isomap)和基于局部的局部线性嵌入方法(Locally Linear Embedding, LLE)进行了对比分析。选取了更有益于保留关键信息的降维方法进行特征降维。
基于12个网页-相关网页
局部线性嵌入方法是一种应用广泛的流形学习方法，本文提出算法的一种改进，并将其应用于空间数据索引。
Locally linear embedding (LLE) is a widely-used manifold learning algorithm, in this paper we improve on the algorithm and put it to use in spatial data index.
针对这个缺点，提出了一种改进的、基于自适应最近邻法的局部线性嵌入方法，数值实验证明算法对于有监督的学习问题，具有较好的适应性。
An adaptive nearest neighbor locally linear embedding algorithm is proposed to overcome this shortage. Experiment results show that the algorithm ADAPTS well the supervised learning problems.
针对该问题，提出基于核局部线性嵌入算法的图像去噪方法。
Aiming at this problem, this paper USES Kernel Locally Linear Embedding (KLLE) algorithm to solve image denoising problem in this paper.
应用推荐