说明：  极限学习机的回归拟合及分类，介绍一个针对SLFN的新算法——极限学习机（Extreme Learning Machine，ELM），该算法随机产生输入层与隐含层间的连接权值及隐含层神经元的阈值，且在训练过程中无需调整，只需要设置隐含层神经元的个数，便可以获得唯一的最优解。与传统的训练方法相比，该方法具有学习速度快、泛化性能好等优点。
(Extreme Learning Machine regression and classification, introduce a new algorithm for SLFN- Extreme Learning Machine (Extreme Learning Machine, ELM), the algorithm randomly generated input layer and hidden layer connection weights between the hidden layer and dollar threshold, and no adjustment in the training process, only need to set the number of hidden layer neurons, they can obtain a unique optimal solution. Compared with traditional training methods, this method has fast learning and good generalization performance.)