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.)

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 (slfns). It only needs to set t

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.)