搜索资源列表
LVQ学习矢量化算法
- LVQ学习矢量化算法源程序 This directory contains code implementing the Learning vector quantization network. Source code may be found in LVQ.CPP. Sample training data is found in LVQ1.PAT. Sample test data is found in LVQTEST1.TST and LVQTEST2.TST. The
co-training
- 半监督学习co-training 回归算法的java代码实现。-COREG is a co-training style semi-supervised regression algorithm, which employs two kNN regressors using different distance metrics to select the most confidently labeled unlabeled examples for each other.
SemiSupervisedLearning
- 第一本全面的半监督学习参考书，里面涵盖了半监督方面的各种算法，应用，以及理论证明-This is a comprehensive reference of semi-surpervised learning, including the algrithms, application, and the proof in theory.
2D_teaching_material
- 这是2010合工大Robocup机器人足球仿真2D技术培训内部培训资料，我找的好长时间才找到，希望对大家有用！-This is the 2010 co-workers big Robocup robot soccer simulation 2D technical training within the training materials, I am looking for a good long time to find the hope for all of us!
CoTrade
- COTRADE算法通过MATLAB编写，通过数据和修改相关技术，实现了传统的协同算法的加强-The package includes the MATLAB code of COTRADE, which is designed for enhancing traditional co-training algorithm by incorporating data editing techniques.
libsvm-3.11
- co-training协同训练算法研究 svm工具箱-co-training self-training
7----Co-training-A-SEMI-SUPERVISED-ENSEMBLE-LEARN
- 7 - Co-training A SEMI-SUPERVISED ENSEMBLE LEARNING ALGORITHM-6-7 - Co-training A SEMI-SUPERVISED ENSEMBLE LEARNING ALGORITHM-6
co-training
- matlab实现co-training算法，数据集mutiple+Features(Matlab implements co-training algorithm, data set mutiple+Features.)
BCI_MI_CSP_DNN
- BCI_MI_CSP_DNN是一种基于matlab的运动图像脑电信号分类程序。 基于matlab深度学习工具箱编写了BCI_MI_CSP_DNN程序 本程序的原理基于CSP和DNN算法 这个程序的性能是基于BCI竞赛II数据集II 提出了一种基于深度学习的运动图像脑电信号分类方法。在预处理原始脑电图信号的基础上，采用共空间模型(CSP)方法提取脑电图特征矩阵，并将其输入深度神经网络(DNN)进行训练和分类。我们的工作在BCI Competition II Dataset III上进行了实