搜索资源列表
KLPP
- 核lpp（局部保持映射）的降维方法。跟Xiaofei He的论文配套-Nuclear lpp (partial maintain mapping) methods of dimensionality reduction. Xiaofei He told the paper supporting
lda
- 非线性降维方法 可以应用于高维数据的机器学习-Nonlinear dimensionality reduction methods can be applied to high-dimensional data, machine learning
pca
- 非线性降维方法 可以应用于高维数据的机器学习-Nonlinear dimensionality reduction methods can be applied to high-dimensional data, machine learning
empca
- EMPCA算法的函数代码，附带有训练测试数据集，用于特征降维等方面。-Algorithm EMPCA function code, attached to the test data set there is training for the characteristics of dimensionality reduction and so on.
npe
- 流形学习算法lle的线性化方法，是一种非监督的降维方法，比lle的优势在于可以将新的样本点映射到低维空间。-Lle manifold learning algorithm of the linearization method, is a non-supervised dimensionality reduction method has the advantage of being more than lle can sample the new point is mapped to the