海量数据挖掘MMDS week4: 推荐系统之数据降维Dimensionality Reduction

http://blog.csdn.net/pipisorry/article/details/49231919

海量数据挖掘Mining Massive Datasets(MMDs) -Jure Leskovec courses学习笔记 推荐系统Recommendation System之降维Dimensionality Reduction

{博客内容：推荐系统有一种推荐称作隐语义模型(LFM, latent factor model)推荐，这种推荐将在下一篇博客中讲到。这篇博客主要讲隐语义模型的基础：降维技术，包括SVD分解等等}

, , ])
B = [[.608, -.459, -.119], [.728, .485, -.485], [2.250, -.500, -.750], [.429, .857, .286]]
for b in B:
print(np.linalg.norm(b))
print(a.dot(b))
print()

PCA

皮皮blog

from:http://blog.csdn.net/pipisorry/article/details/49231919

ref: Anand.Rajaraman-大数据：互联网大规模数据挖掘与分布式处理