搜索资源列表
PCA
- 主元分析算法的matlab实现，可实现数据降温处理，模块完整，可直接应用。-Principal component analysis
pca
- pca算法原理介绍和仿真代码，主要用于数据的聚类，代码时用于图像上的聚类过程，聚类效果很好，就是有点慢-pca algorithm introduces the principle and simulation code, mainly for clustering data, a clustering process images on-time code, clustering works well, is a bit slow
PCA
- 简单PCA算法的matlab实现，两种途径-Simple PCA algorithm of matlab, two different ways
PCA
- 这是基于MATLAB 的神经网络训练算法的源程序，希望对大家有用-This is based on the MATLAB neural network training algorithm source, we hope to be useful
pythonsrc
- 机器学习算法，包括主成分分析方法，奇异值分解，逻辑回归，最小二乘法线性回归，朴素贝叶斯-machine learning algorithm prototype including PCA, SVD, Logic Regression, LMS and Naive Bayes
pca-hmmP
- 利用HMM算法来预测回转窑的喂煤量,以辅助工业现场的判断-Use HMM algorithm to predict the kiln feed coal to assist the industrial field judge
PCA
- 数据挖掘中很重要的主成分分析(PCA)算法-Principal Component Algorithm in Data Mining
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
pca11
- 使用matlab编程实现PCA算法，此算法经过测试，没有问题，可以放心使用-Use matlab programming PCA algorithm that has been tested, no problem, you can rest assured that use
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.
PCA
- python PCA算法。 以及主成分分析的相关文档，资料，数据集。-python PCA algorithm.
SVM_GUI_3.1[mcode]
- faruto编写的基于libsvm3.1的SVM_GUI，可用于SVM分类及相关回归分析，已经集成了GA及PSO参数寻优算法及PCA算法，提供的是GUI版本及与之对应的源码版本-SVM_GUI and the program of SVM_Code,base on the version of the Libsvm 3.1，using the GA and PSO algorithm to improve
Change-Detection-Code
- 遥感影像变化检测经典算法(IR-MAD、MAD、CVA、PCA),另外进行了算法的Demo和精度等计算评价（OA、Kappa、AUC、ROC）-Remote sensing image change detection classical algorithm (IR-MAD, MAD, CVA, PCA), were additionally algorithms and calculation accuracy Demo Assessment (OA, Kappa, AUC, ROC)
降维code
- 了解降维、特征筛选等基本原理 掌握PCA、SVD、LAD和NMF等算法实现及应用(Understand the basic principles of dimensionality reduction and feature selection Master the algorithm implementation and application of PCA, SVD, lad and NMF)
PCA+mnist
- 基于python，利用主成分分析（PCA）和K近邻算法（KNN）在MNIST手写数据集上进行了分类。 经过PCA降维，最终的KNN在100维的特征空间实现了超过97%的分类精度。(Based on python, it uses principal component analysis (PCA) and K nearest neighbor algorithm (KNN) to classify on the MNIST handwritten data set. After PCA dime
PCA算法
- 对高维数据进行特征两提取,提高数据分类速度,可用于故障诊断数据的特征量提取.