搜索资源列表
Elm_KElm
- Elm和KernelElm算法matlab实现，带有详细注释，并且提供了UCI数据集多个数据库供测试-Elm and Kelm algorithm, with detailed notes, and provides multiple UCI data set for testing
KELM
- 采用核函数的ELM算法，可以获得更好的效果-ELM algorithm USES the kernel function, can obtain better results
kelml
- kelm matlab程序 带有中文注释 学习参考的源码(The kelm matlab program has the source code with annotation learning reference)
KELM
- 可用作数据的拟合和分类。核极限学习机采用了核函数，将数据投射到高维空间分类(It can be used for data fitting and classification. Kernel extreme learning machine uses kernel function to project data onto high-dimensional space.)
wind power forecasting based on EWT-KELM
- 针对短期风电功率预测，提出一种基于经验小波变换预处理的核极限学习机组合预测方法。首先采用 EWT 对风电场实测风速数据进行自适应分解并提取具有傅立叶紧支撑的模态信号分量，针对每个分量分别构建 KELM 预测模型，最后对各个预测模型的输出进行叠加得到风速预测值并根据风电场风功特性曲线可得对应风电功率预测值。(Aiming at short-term wind power prediction, a kernel-based learnin
ML-KELM1.0
- 多核极限学习器，是一种前馈神经网络，能逼近任意连续目标函数或分类任务重的任何复杂决策边界(Multi-kernel limit learner is a feedforward neural network, which can approach any complex decision boundary of any continuous objective function or classification task)
KELM
- 核极限学习机是一种单隐层前馈神经网络(the single-hidden layer feedforward neural networks,SLFNs),其只需要设置隐藏层节点数,然后采用最小二乘法计算出权值即可。因此,核极限学习机在学习速度和泛化能力上具有很大优势。(Kernel limit learning machine is a single hidden layer feedforward neural networks (
53607888elm_kernel_trainapredict
- 核极限学习机程序，可以直接调用，满足分类要求。想换求KELM回归程序。(Kernel limit learning machine program can be called directly to meet the classification requirements.Want to change KELM regression program.)