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DimensionalityReduction_alo_codes

网上关于各种降维算法的资料参差不齐,同时大部分不提供源代码;在此通过借鉴资料实现了一些经典降维算法的Demo(python),同时也给出了参考资料的链接。

降维算法 资料链接 展示
PCA https://blog.csdn.net/u013719780/article/details/78352262 https://blog.csdn.net/u013719780/article/details/78352262 https://blog.csdn.net/weixin_40604987/article/details/79632888 PCA
KPCA https://blog.csdn.net/u013719780/article/details/78352262 https://blog.csdn.net/u013719780/article/details/78352262 https://blog.csdn.net/weixin_40604987/article/details/79632888 KPCA
LDA https://blog.csdn.net/ChenVast/article/details/79227945 https://www.cnblogs.com/pinard/p/6244265.html LDA
MDS https://blog.csdn.net/zhangweiguo_717/article/details/69663452?locationNum=10&fps=1 MDS Tensor-MDS
ISOMAP https://blog.csdn.net/zhangweiguo_717/article/details/69802312 http://www-clmc.usc.edu/publications/T/tenenbaum-Science2000.pdf ISOMAP
LLE https://blog.csdn.net/scott198510/article/details/76099630 https://www.cnblogs.com/pinard/p/6266408.html?utm_source=itdadao&utm_medium=referral LLE
TSNE http://bindog.github.io/blog/2018/07/31/t-sne-tips/ TSNE
AutoEncoder 无  AutoEncoder
FastICA https://blog.csdn.net/lizhe_dashuju/article/details/50263339
SVD https://blog.csdn.net/m0_37870649/article/details/80547167 https://www.cnblogs.com/pinard/p/6251584.html
LE https://blog.csdn.net/hustlx/article/details/50850342# https://blog.csdn.net/jwh_bupt/article/details/8945083 LE

环境: python3.6 ubuntu18.04(windows10) 需要的库: numpy sklearn tensorflow matplotlib

  • 每一个代码都可以单独运行,但是只是作为一个demo,仅供学习使用
  • 其中AutoEncoder只是使用AutoEncoder简单的实现了一个PCA降维算法,自编码器涉及到了深度学习领域,其本身就是一个非常大领域
  • LE算法的鲁棒性极差,对近邻的选择和数据分布十分敏感

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PCA、LDA、MDS、LLE、TSNE等降维算法的python实现

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