| Radial Basis Function/RBF |
径向基函数 |
| Random Forest Algorithm |
随机森林算法 |
| Random walk |
随机漫步 |
| Recall |
查全率/召回率 |
| Receiver Operating Characteristic/ROC |
受试者工作特征 |
| Rectified Linear Unit/ReLU |
线性修正单元 |
| Recurrent Neural Network |
循环神经网络 |
| Recursive neural network |
递归神经网络 |
| Reference model |
参考模型 |
| Regression |
回归 |
| Regularization |
正则化 |
| Regularizer |
正则化项 |
| Reinforcement learning/RL |
强化学习 |
| Relative entropy |
相对熵 |
| Reparametrization |
重参数化 |
| Representation learning |
表征学习 |
| Representer theorem |
表示定理 |
| Reproducing Kernel Hilbert Space/RKHS |
再生核希尔伯特空间 |
| Re-sampling |
重采样法 |
| Rescaling |
再缩放 |
| Reservoir computing |
储层计算 |
| Residual Mapping |
残差映射 |
| Residual Network |
残差网络 |
| Restricted Boltzmann Machine/RBM |
受限玻尔兹曼机 |
| Restricted Isometry Property/RIP |
限定等距性 |
| Reverse mode accumulation |
反向模式累加 |
| Re-weighting |
重赋权法 |
| Ridge regression |
岭回归 |
| Robustness |
稳健性/鲁棒性 |
| Root node |
根结点 |
| Rule Engine |
规则引擎 |
| Rule learning |
规则学习 |