搜索资源列表
pattern_recognition_v6.1
- 完整的模式识别库，包括矩阵运算，各种模式识别算法，如K均值、SVM、RVM、NN、LDA等
prtools3.1.7.rar
- 模式识别 MATLAB 的工具箱,比较实用,包括SVM,ICA,PCA,NN等等模式识别算法.,Pattern Recognition Toolbox for MATLAB, more practical, including the SVM, ICA, PCA, NN pattern recognition algorithm and so on.
libsvm-2.89
- 是一種線性方成的分類器。SVM透過統計的方式將雜亂的資料以NN的方式分成兩類，以便處理。LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. -Main features of LIBLINEA
DetectionLibrary
- Chesnokov Yuriy写的人脸检测库，内容涵盖肤色检测、运动估计、SVM分类、PCA/LDA/ICA特征提取以及神经网络分类器等。-The article demonstrates face detection SSE optimized C++ library for color and gray scale data with skin detection, motion estimation for faster processing, small sized SVM and NN
GRNN
- 泛化回归神经网络GRNN(generalized regression NN)应用实例，适合学习使用。-Generalized regression neural network GRNN (generalized regression NN) application examples for learning to use.
Classification-toolbox
- 通过降维处理，高维数据的分类一般可以转换为2维数据分类。此源码包含一个2维-2类数据分类工具箱。包括：ML，K-NN，SVM，LS，DB-Through the dimension reduction processing, high dimensional data classification commonly can convert to 2 d data classification. This source includes a 2 d-two kinds of data classi
ELM-NN
- 基于极限学习机(ELM)的岩性识别。该算法是一种新的单隐层前馈神经网络(sLFNs)学习算法，不但可以简化参数选择过程，而且可以提高网络的训练速度。-Based on the traditional support vector machine (sVM) training is slow, difficult issues such as parameter selection, extreme learning machine is proposed based on (ELM) of li
CM
- 里面包括了关于TCM的各种算法，有TCM-NC算法，TCM-NN算法，TCM-SVM算法。对研究TCM算法的同学来说，很有帮助哦！-Inside, including a variety of algorithms about TCM, TCM-NC algorithm, TCM-NN algorithm, TCM-SVM algorithm. For students who study TCM algorithm helpful!
Pattern_Recognition
- 自己在硕士期间用到的各种模式识别，机器学习，数据挖掘算法的matlab程序。C4_5,NN，SVM，adaboost,KNN等-During their Master used a variety of pattern recognition, machine learning, data mining algorithm matlab program. C4_5, NN, SVM, adaboost, KNN, etc.
svm4
- svm sdd nn ddn j jij jiihbv ffy
activity-recognition-based-on-SVM
- 基于支持向量机的人类活动识别，以日常生活中的10个活动进行识别。-Support Vector Machine (SVM) was first proposed in 1995 by Cortes and Vapnik [15] for solving classification and regression problems. The solving strategy of SVM on the multiple classification problems is com
nn_svm
- 采用NN-SVM算法进行分类识别,有数据包和程序文件。-usingNN-SVM algorithm classification
Recognition
- 将数量较少的故障样本分为训练集和测试集，实现故障的分类和识别(A small number of fault samples are divided into training set and test set to realize fault classification and recognition.)