资源列表
hierarchical_clustering
- python数据挖掘hierarchical_clustering-python data mining hierarchical_clustering
chapter11code
- python 数据挖掘 chapter-python data mining chapter11
chapter12code
- python数据分析与实战chapter12-python data analysis and practical chapter12
chapter13code
- python数据分析与实战chapter13-python data analysis and practical chapter13
LDA
- LDA是监督式的降维算法，输入时需要为每一个数据打上标签信息。最多可以降到n-1维（n为数据点个数）-LDA Algorithm is used to realize dimensionality reduction. It can be used in the amount of projects such as face recognition.
mySVD
- svd算法可用于降维，也可用于pca的分解中。-SVD algorithm can be used to complete the PCA algorithm. It can also be used to realize dimensionality reduction.
qiyezhu
- 企业主经典投资选股代码，帮助投资人在股票池中选择股票，运用企业主交易原则-this code is to help trader to stock stock pool by using company holder strategy.
SVM
- 支持向量机神经网络的信息粒化时序回归预测代码案列，代码易于修改-Support Vector Machines Neural Network Information granulated series regression predictive code text column, easy to modify the code
low-rank_subspace_clustering
- 低秩子空间聚类。来源是Favaro在CVPR11年发表的一篇论文。-Low rank subspace clustering.
lrr
- 求解低秩表示模型。使用ADM求解样本的低秩表示矩阵。-Solving low rank representation model.
DS3_v1.1
- 基于相异性的稀疏子集选择。作者是大名鼎鼎的Ehsan Elhamifar。-Dissimilarity-based Sparse Subset Selection (DS3) is an algorithm based on simultaneous sparse recovery for finding data/model representatives a large collection of data/models.
SMCE_v1.2
- 稀疏流形聚类。作者是大名鼎鼎的Ehsan Elhamifar。-Sparse Manifold Clustering and Embedding (SMCE) is an algorithm based on sparse representation theory for clustering and dimensionality reduction of data lying in a union of nonlinear manifolds.