搜索资源列表
huxinxi
- 粗糙集互信息的约简代码。基于MATLAB。苗夺谦的论文的方法。-Mutual Reduction of rough set code information. Based on MATLAB. Methods Miao Duoqian papers.
xyle
- 拉普拉斯降维方法，是非线性数据降维方法，通过构建相似关系图来重构数据局部流形结构特征。-Laplace dimension reduction method is non-linear data dimensionality reduction method, by constructing a graph similar to reconstruct the structure of local manifoldof the data.
drtoolbox
- Matlab dimension reduction toolbox
PCA-AND-PNN
- 应用主成分分析对数据降维，将得到的数据用于概率神经网络训练，进行模式识别。对于一组新数据，先计算主成分得分，再输入训练好的概率神经网络，就会得到识别结果，即改组数据属于何种类别。-Principal component analysis of the data reduction, data will be obtained for the probabilistic neural network training, pattern recognition. For a new set of d
UQ-PyL_Linux.tar
- 优化计算程序包,适用于水文及生态模型的优化计算及参数校准。-Uncertainty quantification (UQ) refers to quantitative characterization and reduction of uncertainties present in computer model simulations. It is widely used in engineering and geophysics fields to assess and predict t
PAC--Datamining
- PCA降维算法应用大数据挖掘中，在大数据环境下实现数据的降维，可按需要自行修改代码-PCA dimensionality reduction algorithm in data mining, in the big data environment for data dimension reduction, according to need to modify the code itself
mani
- 此代码是关于流形学习，数据降维，代码中含有的主要方法是PCA，KPCA，MDS，KMDS，Laplacian等等，且代码作了可视化处理，界面效果完美-This code is on the manifold learning, data dimensionality reduction, the main method code is contained in PCA, KPCA, MDS, KMDS, Laplacian, etc., and the code visualization ma
clsf_dpd1
- 基于粗糙集和遗传算法的属性约简，包含核及不可区分关系等求解-Attribute reduction based on rough sets and genetic algorithm, including nuclear and indistinguishable relationship to solve
neighborhood-classifier
- 依据Neighborhood classifier编写的.m程序-Metric space Neighborhood Rough set Reduction Classifier Norm
dimensionality-reduction-and-k-means
- 1.使用k-svd对数据进行稀疏表示，降维 2.使用k-means对上述数据聚类-1.use k-svd to reduce the dimensions of data 2.clster the data by k-means
roughset-into-weka
- 可以嵌入weka中的粗糙集约简算法，进一步扩充weka的数据挖掘功能-Weka can be embedded in the rough set reduction algorithm to further expand weka data mining functions
MLRforSSVEPDemo
- 对于CK信号进行降维，同时也有线性回归方法，里面有一个例子供大家学习-CK signal for dimensionality reduction, but also a linear regression method, which has an example for everyone to learn
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.
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.
NJU-SSDR
- 半监督判别分析（SSDR），是南京大学数据挖掘研究所提出的一种新的半监督降维算法，对于数据挖掘和类别样本的获取有着十分重要的借鉴价值。-A semi-supervised discriminant analysis (SSDR), is one of the types of data mining research institute of nanjing university puts forward new a semi-supervised dimensionality reductio
lwpr
- LWPR 局部加权投影回归算法，是一种高效的数据降维方法，也能用于预测方法研究。 -LWPR is an effective dimensionality reduction approach. It can be used for prediction.
Data-dimensionality-reduction
- 该压缩文件为部分数据降维方法，有LTSA、HHLLE、ISOMAP、LLTSA、LLP-The compressed file for the partial data dimensionality reduction method, there are LTSA, HHLLE, ISOMAP, LLTSA, LLP
project
- 数据挖掘，推荐系统，堆叠降噪自编码器，逻辑回归(Data mining, recommender systems, stack noise reduction, self coder, logic regression)
LDA_ FDA_with_tutorial
- LDA降维是常用的降维手段之一，是常用的有监督学习降维工具。这个文件对其产生W后的使用进行了简要说明，使用W进行最终的降维可以得到十分漂亮的分析结果（在数据分布符合假设分析的情况下。）(LDA dimension reduction is one of the commonly used dimensionality reduction methods. It is a commonly used supervised learning dimensionality reduction tool