搜索资源列表
pca
- 利用python实现主成分分析，主要用在图像处理等领域-Use python to achieve the principal component analysis, mainly used in the field of image processing, etc.
mypca
- 基于Python在Swiss roll上实现PCA，并应用LE算法进行改进。-Python implementation PCA on the Swiss roll, and apply the LE algorithm based on improved.
PCA_Eigen
- Python implementation of PCA by utilizing Eigen value decomposition technique.
PCA
- Python实现PCA将数据转化成前K个主成分的伪码大致如下: ''' 减去平均数计算协方差矩阵计算协方差矩阵的特征值和特征向量将特征值从大到小排序保留最大的K个特征(Python PCA data into pseudo code before the K principal components are as follows: the characteristics of 'average minus the covariance matrix to calculate the covari
kernel_eca-master
- Kernel Entropy Component Analysis,KECA方法的作者R. Jenssen自己写的MATLAB代码，文章发表在2010年5月的IEEE TPAMI上面-Kernel Entropy Component Analysis, by R. Jenssen, published in IEEE TPAMI 2010.(We introduce kernel entropy component analysis (kernel ECA) as a new method fo
face-SVM
- 用PCA和SVM实现人脸识别，是经典的人脸识别Python代码(Face recognition using PCA and SVM)
EnglishChuLi
- 利用python编写的文本预处理的程序，包含了每一步的实现代码，分为删除标点符号、删除停用词、相似度计算、PCA降维、聚类以及可视化等，运行环境为pytharm，python3开发环境(The text preprocessing program written by Python contains every step of implementation code, which is divided into delete punctuation marks, delete stop word
ChineseChuLi
- 中文文本处理的python程序，包括分词、删除特殊字符、删除停用词、爬虫程序、PCA降维、Kmean聚类、可视化等(Python programs for Chinese text processing, including participle, deleting special characters, deleting disuse words, crawler programs, PCA dimensionality reduction, Kmean clustering, visuali
机器学习常用方法
- 机器学习常用方法的python实现，包括PCA，随机森林，决策树，层次聚类，kmeans，KNN，线性感知机等(Python implementation of common machine learning methods, including PCA, random forest, decision tree, hierarchical clustering, kmeans, KNN, linear perceptron, etc.)