搜索资源列表
pca-matlab
- pca算法的源代码。在做人工智能与模式识别的朋友必须的。用于降维。
FisherFace1
- 最经典的人脸识别中的fisherface代码,在此之前要对特征空间降维,通常采用PCA降维,此代码基于降维实现类间与类内比值的最大化。
PCALDA
- PCA+LDA经典人脸识别算法,先用PCA降维,再用LCA降维-PCA+ LDA classical face recognition algorithms, first PCA dimension reduction, reuse LCA dimension reduction
empca2.tar
- 模式分类中应用到的PCA算法,包括其奇异值分解SVD算法。可用来降维提取主元素等。-pattern classification applied to the PCA algorithm, including its SVD singular value decomposition algorithm. Can be used to take down the main Viti Levu and other elements.
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
PCA
- 用于模式识别中的PCA降维输入数据data和option。data是一个矩阵,每一行代表一个样本。option是选择降维到多少维。-[eigvector, eigvalue] = PCA(data, options) [eigvector, eigvalue] = PCA(data)
PCA
- 主成份分析,一个最经典的无监督学习算法,也是最常用的线性降维方法-PCA
DCT
- 本文设计基于DCT的人脸识别系统,首先结合当今人脸识别的背景和发展状况讨论了人脸识别的研究内容及在各方面的应用;然后研究了人脸识别进行预处理,讨论了人脸识别预处理的其他方法,分析各种方法的利弊,最后采用DCT(离散余弦变换)实现人脸图像预处理中的降维处理;接下来对人脸图像的特征提取进行了研究,简单叙述了几何特征提取和代数特征提取,同时深入研究了基于DCT和PCA变换的人脸图像特征提取,从而实现是否对人脸识别系统识别率有所提高的研究;对于分类器的选择,本文对两种分类器进行了探讨,即最近邻分类器和B
pca
- pca主成分分析,matlab程序,用于图像特征提取,降维等 有中文注释-Principal component analysis
PCA
- 该程序主要是用于模式识别对样本进行降维处理,该程序是通过PCA的方法实现降维-The program is mainly used for pattern recognition to reduce the dimension of the samples, the program is achieved through the method of PCA dimensionality reduction
KNN
- 基于PCA降维的KNN,最近邻分类matlab实现。-PCA dimensionality reduction based the KNN, the nearest neighbor classification matlab.
K---NN
- 以著名的wine数据作为实验样本。包括k-NN算法,交叉验证,PCA降维等。-With the famous wine data as experimental samples.K- NN algorithm, cross validation, PCA dimension reduction, etc.
pca-bp
- 在建模前先将数据利用PCA进行降维,将降维后的数据作为BP神经网络的输入因子,对数据进行拟合。-Before the first data modeling use PCA dimensionality reduction, the reduced dimensionality of the data as the input factor BP neural network, the data fitting.
gonglv_pca
- MATLAB编程,提取LFP功率特征,采用PCA降维,实现不同颜色数据分类-MATLAB programming, LFP power feature extraction using PCA dimensionality reduction to achieve different color data classification
pca
- 机器学习算法,利用PCA来简化数据,降维技术,主成分分析-Machine learning algorithm, using PCA to simplify data dimensionality reduction techniques, principal component analysis
PCA_wine
- 使用PCA降维的一种用于葡萄酒分类的经典算法,给大家参考下-Using PCA dimensionality reduction of a wine classification of the classic algorithm, to your reference
PCA
- 主成分分析,空间降维的人工智能算法,也能用来去相关性,在图像等信号处理常用-Principal component analysis, spatial dimensionality reduction of artificial intelligence algorithms, but also can come and relevance, in the image signal processing such as common
knn
- 首先对minist数据集进行pca降维,然后对降维后的数据进行KNN分类(First, the Minist data set is reduced by PCA, and then the data of the reduced dimension is classified by KNN)
PCA0118
- PCA降维,将特征以二维矩阵形式输入,对特征进行降维处理。(PCA dimension reduction, the characteristics of a two-dimensional matrix input, the feature dimensionality reduction.)
k_means
- 主成分分析(Principal Component Analysis,PCA), 是一种统计方法。通过正交变换将一组可能存在相关性的变量转换为一组线性不相关的变量,转换后的这组变量叫主成分。(It is a statistical method. Through orthogonal transformation, a set of variables that can be correlated can be transformed into a group of linearly irrel