人工智能专业术语Artificial-Intelligence-Terminology R
| 英文/缩写 | 汉语 |
|---|---|
| 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 |
人工智能专业术语
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