搜索资源列表
B-ELM
- Bidirectional extreme learning machine - B-ELM Y. Yang, Y. Wang, and X. Yuan, "Bidirectional extreme learning machine for regression problem and its learning effectiveness," IEEE Transactions on Neural Networks and Learning Systems, Vol. 23, pp.
Weighted-ELM-Codes-for-Binary-Problems
- Weighted ELM for imbalanced datasets - Weighted-ELM W. Zong, G.-B. Huang, and Y. Chen, “Weighted extreme learning machine for imbalance learning,” Neurocomputing, vol. 101, pp. 229-242, 2013.
ELM
- 极限学习机程序代码，可以进行拟合与分类，该算法结构简单，比BP等神经网络号-extreme learning machine
elm2
- 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 Mach
image-segment
- 这是用ELM（极限学习机）做的关于图像识别的分类实验，有数据，有程序，有训练时间，测试时间和精度-It is used ELM (Extreme Learning Machine) to do experiments on the classification of image recognition, has data, procedures, training time, test time and accuracy
SaDE-ELM
- 基于差分进化的极限学习机 基于差分进化的极限学习机-Based on Differential Evolution Extreme Learning Machine
OS-ELM
- 极限学习机（extreme learning machine）ELM是一种简单易用、有效的单隐层前馈神经网络SLFNs学习算法。2004年由南洋理工大学黄广斌副教授提出。传统的神经网络学习算法（如BP算法）需要人为设置大量的网络训练参数，并且很容易产生局部最优解。极限学习机只需要设置网络的隐层节点个数，在算法执行过程中不需要调整网络的输入权值以及隐元的偏置，并且产生唯一的最优解，因此具有学习速度快且泛化性能好的优点。-ELM extreme learning machine (extreme l
ELM
- ELMExtreme Learning Machine
elm
- 简单易学的机器学习算法——极限学习机(ELM)(Extreme Learning Machine)