# Letter M
[*Return*](https://github.com/SyncedAI00/Artificial-Intelligence-Terminology/blob/master/README.md)
索引编号|英文术语|中文翻译|常用缩写|来源&扩展|备注
---|---|---|---|---|---
AITD-01087|Machine Learning Model|机器学习模型||[1]||
AITD-01088|Machine Learning|机器学习|ML|[[1]](https://www.nature.com/articles/s41557-021-00716-z)|机器学习|
AITD-01089|Machine Translation|机器翻译|MT|[[1]](https://www.jiqizhixin.com/articles/2018-01-13-5)||
AITD-01090|Macro Average|宏平均||[1]||
AITD-01091|Macro-F1|宏F1||[1]||
AITD-01092|Macro-P|宏查准率||[1]||
AITD-01093|Macron-R|宏查全率||[1]||
AITD-01094|Mahalanobis Distance|马哈拉诺比斯距离||[1]||
AITD-01095|Main Diagonal|主对角线||[1]||
AITD-01096|Majority Voting|绝对多数投票||[1]||
AITD-01097|Majority Voting Rule|多数表决规则||[1]||
AITD-01098|Manhattan Distance|曼哈顿距离||[1]||
AITD-01099|Manifold|流形||[1]||
AITD-01100|Manifold Assumption|流形假设||[1]||
AITD-01101|Manifold Learning|流形学习||[1]||
AITD-01102|Manifold Tangent Classifier|流形正切分类器||[1]||
AITD-01103|Margin|间隔||[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00169/978-1-78801-789-3)|统计|
AITD-01104|Margin Theory|间隔理论||[1]||
AITD-01105|Marginal Distribution|边缘分布||[1]||
AITD-01106|Marginal Independence|边缘独立性||[1]||
AITD-01107|Marginal Likelihood|边缘似然函数||[1]||
AITD-01108|Marginal Probability Distribution|边缘概率分布||[1]||
AITD-01109|Marginalization|边缘化||[1]||
AITD-01110|Markov Blanket|马尔可夫毯||[1]||
AITD-01111|Markov Chain|马尔可夫链||[1]||
AITD-01112|Markov Chain Monte Carlo|马尔可夫链蒙特卡罗|MCMC|[[1]](https://www.jiqizhixin.com/articles/2017-12-24-6)||
AITD-01113|Markov Decision Process|马尔可夫决策过程|MDP|[1]||
AITD-01114|Markov Network|马尔可夫网络||[1]||
AITD-01115|Markov Process|马尔可夫过程||[1]||
AITD-01116|Markov Property|马尔可夫性质||[1]||
AITD-01117|Markov Random Field|马尔可夫随机场|MRF|[1]||
AITD-01118|Mask|掩码||[1]||
AITD-01119|Mask Language Modeling|掩码语言模型化||[1]||
AITD-01120|Masked Self-Attention|掩蔽自注意力||[1]||
AITD-01121|Mathematical Optimization|数学优化||[1]||
AITD-01122|Matrix|矩阵||[1]||
AITD-01123|Matrix Calculus|矩阵微积分||[1]||
AITD-01124|Matrix Completion|矩阵补全||[1]||
AITD-01125|Matrix Decomposition|矩阵分解||[1]||
AITD-01126|Matrix Inversion|逆矩阵||[1]||
AITD-01127|Matrix Product|矩阵乘积||[1]||
AITD-01128|Max Norm|最大范数||[1]||
AITD-01129|Max Pooling|最大汇聚||[[1]](https://www.jiqizhixin.com/articles/2017-10-02-5)||
AITD-01130|Maxima|极大值||[1]||
AITD-01131|Maximal Clique|最大团||[1]||
AITD-01132|Maximization|极大||[1]||
AITD-01133|Maximization Step|M步||[1]||
AITD-01134|Maximization-Maximization Algorithm|极大-极大算法||[1]||
AITD-01135|Maximum A Posteriori|最大后验||[1]||
AITD-01136|Maximum A Posteriori Estimation|最大后验估计|MAP|[1]||
AITD-01137|Maximum Entropy Model|最大熵模型||[1]||
AITD-01138|Maximum Likelihood|极大似然||[1]||
AITD-01139|Maximum Likelihood Estimation|极大似然估计|MLE|[[1]](https://www.jiqizhixin.com/articles/2018-01-09-6)||
AITD-01140|Maximum Likelihood Method|极大似然法||[1]||
AITD-01141|Maximum Margin|最大间隔||[1]||
AITD-01142|Maximum Mean Discrepancy|最大平均偏差||[1]||
AITD-01143|Maximum Posterior Probability Estimation|最大后验概率估计|MAP|[1]||
AITD-01144|Maximum Weighted Spanning Tree|最大带权生成树||[1]||
AITD-01145|Maxout|Maxout||[1]||
AITD-01146|Maxout Unit|Maxout单元||[1]||
AITD-01147|Mean|均值||[1]||
AITD-01148|Mean Absolute Error|平均绝对误差||[1]||
AITD-01149|Mean And Covariance RBM|均值和协方差RBM||[1]||
AITD-01150|Mean Filed|平均场||[1]||
AITD-01151|Mean Filter|均值滤波||[1]||
AITD-01152|Mean Pooling|平均汇聚||[1]||
AITD-01153|Mean Product of Student t-Distribution|学生 t 分布均值乘积||[1]||
AITD-01154|Mean Squared Error|均方误差||[1]||
AITD-01155|Mean-Covariance Restricted Boltzmann Machine|均值-协方差受限玻尔兹曼机||[1]||
AITD-01156|Mean-Field|平均场||[1]||
AITD-01157|Meanfield|均匀场||[1]||
AITD-01158|Measure Theory|测度论||[1]||
AITD-01159|Measure Zero|零测度||[1]||
AITD-01160|Median|中位数||[1]||
AITD-01161|Memory|记忆||[1]||
AITD-01162|Memory Augmented Neural Network|记忆增强神经网络|MANN|[1]||
AITD-01163|Memory Capacity|记忆容量||[1]||
AITD-01164|Memory Cell|记忆元||[1]||
AITD-01165|Memory Network|记忆网络|MN|[1]||
AITD-01166|Memory Segment|记忆片段||[1]||
AITD-01167|Mercer Kernel|Mercer 核||[1]||
AITD-01168|Message|消息||[1]||
AITD-01169|Message Passing|消息传递||[1]||
AITD-01170|Message Passing Neural Network|消息传递神经网络|MPNN|[1]||
AITD-01171|Meta-Learner|元学习器||[1]||
AITD-01172|Meta-Learning|元学习| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00311/978-1-78801-789-3)| |
AITD-01173|Meta-Optimization|元优化||[1]||
AITD-01174|Meta-Rule|元规则||[1]||
AITD-01175|Metric|指标| |[[1]](https://www.nature.com/articles/s41557-021-00716-z)[[2]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00016/978-1-78801-789-3)| |
AITD-01176|Metric Learning|度量学习||[1]||
AITD-01177|Micro Average|微平均||[1]||
AITD-01178|Micro-F1|微F1||[1]||
AITD-01179|Micro-P|微査准率||[1]||
AITD-01180|Micro-R|微查全率||[1]||
AITD-01181|Min-Max Normalization|最小最大值规范化||[1]||
AITD-01182|Mini-Batch Gradient|小批量梯度||[1]||
AITD-01183|Mini-Batch Gradient Descent|小批量梯度下降法||[1]||
AITD-01184|Mini-Batch SGD|小批次随机梯度下降||[1]||
AITD-01185|Minibatch|小批量||[1]||
AITD-01186|Minibatch Stochastic|小批量随机||[1]||
AITD-01187|Minima|极小值||[1]||
AITD-01188|Minimal Description Length|最小描述长度|MDL|[1]||
AITD-01189|Minimax Game|极小极大博弈||[1]||
AITD-01190|Minimum|极小点||[1]||
AITD-01191|Minkowski Distance|闵可夫斯基距离||[1]||
AITD-01192|Misclassification Cost|误分类代价||[1]||
AITD-01193|Mixing|混合||[1]||
AITD-01194|Mixing Time|混合时间||[1]||
AITD-01195|Mixture Density Network|混合密度网络||[1]||
AITD-01196|Mixture Distribution|混合分布||[1]||
AITD-01197|Mixture of Experts|混合专家模型||[1]||
AITD-01198|Mixture-of-Gaussian|高斯混合||[1]||
AITD-01199|Modality|模态||[1]||
AITD-01200|Mode|峰值||[1]||
AITD-01201|Model|模型||[1]||
AITD-01202|Model Averaging|模型平均||[1]||
AITD-01203|Model Collapse|模型坍塌||[1]||
AITD-01204|Model Complexity|模型复杂度||[1]||
AITD-01205|Model Compression|模型压缩||[1]||
AITD-01206|Model Identifiability|模型可辨识性||[1]||
AITD-01207|Model Parallelism|模型并行||[1]||
AITD-01208|Model Parameter|模型参数||[1]||
AITD-01209|Model Predictive Control|模型预测控制|MPC|[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00340/978-1-78801-789-3)| |
AITD-01210|Model Selection|模型选择||[[1]](https://www.nature.com/articles/s41557-021-00716-z)||
AITD-01211|Model-Agnostic Meta-Learning|模型无关的元学习|MAML|[1]||
AITD-01212|Model-Based Learning|有模型学习||[1]||
AITD-01213|Model-Based Reinforcement Learning|基于模型的强化学习||[1]||
AITD-01214|Model-Free Learning|免模型学习||[1]||
AITD-01215|Model-Free Reinforcement Learning|模型无关的强化学习||[1]||
AITD-01216|Moment|矩||[1]||
AITD-01217|Moment Matching|矩匹配||[1]||
AITD-01218|Momentum|动量||[[1]](https://www.jiqizhixin.com/articles/2017-07-01-4)||
AITD-01219|Momentum Method|动量法||[1]||
AITD-01220|Monte Carlo|蒙特卡罗||[1]||
AITD-01221|Monte Carlo Estimate|蒙特卡罗估计||[1]||
AITD-01222|Monte Carlo Integration|蒙特卡罗积分||[1]||
AITD-01223|Monte Carlo Method|蒙特卡罗方法||[1]||
AITD-01224|Moore's Law|摩尔定律||[1]||
AITD-01225|Moore-Penrose Pseudoinverse|Moore-Penrose 伪逆||[1]||
AITD-01226|Moral Graph|端正图/道德图||[1]||
AITD-01227|Moralization|道德化||[1]||
AITD-01228|Most General Unifier|最一般合一置换||[1]||
AITD-01229|Moving Average|移动平均|MA|[1]||
AITD-01230|Multi-Armed Bandit Problem|多臂赌博机问题||[1]||
AITD-01231|Multi-Class Classification|多分类||[1]||
AITD-01232|Multi-Classifier System|多分类器系统||[1]||
AITD-01233|Multi-Document Summarization|多文档摘要||[1]||
AITD-01234|Multi-Head Attention|多头注意力||[1]||
AITD-01235|Multi-Head Self-Attention|多头自注意力||[1]||
AITD-01236|Multi-Hop|多跳||[1]||
AITD-01237|Multi-Kernel Learning|多核学习||[1]||
AITD-01238|Multi-Label Classification|多标签分类||[1]||
AITD-01239|Multi-Label Learning|多标记学习||[1]||
AITD-01240|Multi-Layer Feedforward Neural Networks|多层前馈神经网络||[1]||
AITD-01241|Multi-Layer Perceptron|多层感知机|MLP|[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00340/978-1-78801-789-3)[[2]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00398/978-1-78801-789-3)[[3]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00372/978-1-78801-789-3)||
AITD-01242|Multi-Nominal Logistic Regression Model|多项对数几率回归模型||[1]||
AITD-01243|Multi-Prediction Deep Boltzmann Machine|多预测深度玻尔兹曼机||[1]||
AITD-01244|Multi-Response Linear Regression|多响应线性回归|MLR|[1]||
AITD-01245|Multi-View Learning|多视图学习||[1]||
AITD-01246|Multicollinearity|多重共线性||[1]||
AITD-01247|Multimodal|多峰值||[1]||
AITD-01248|Multimodal Learning|多模态学习||[1]||
AITD-01249|Multinomial Distribution|多项分布||[1]||
AITD-01250|Multinoulli Distribution|Multinoulli分布||[1]||
AITD-01251|Multinoulli Output Distribution|Multinoulli输出分布||[1]||
AITD-01252|Multiple Dimensional Scaling|多维缩放||[1]||
AITD-01253|Multiple Linear Regression|多元线性回归|MLR|[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00311/978-1-78801-789-3)[[2]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00340/978-1-78801-789-3)[[3]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00206/978-1-83916-023-3)|统计|
AITD-01254|Multitask Learning|多任务学习||[1]||
AITD-01255|Multivariate Decision Tree|多变量决策树||[1]||
AITD-01256|Multivariate Gaussian Distribution|多元高斯分布||[1]||
AITD-01257|Multivariate Normal Distribution|多元正态分布||[1]||
AITD-01258|Mutual Information|互信息||[1]||
AITD-02351|Machine-Readable Data|机器可读的数据| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00169/978-1-78801-789-3)| |
AITD-02352|Mae|平均绝对误差|MAE|[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00076/978-1-78801-789-3)| |
AITD-02353|Mahalanobis Distances|马氏距离| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00311/978-1-78801-789-3)|统计|
AITD-02354|Matrices|矩阵| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00037/978-1-78801-789-3)|数学|
AITD-02355|Matthews Correlation Coefficient|马修斯相关系数|MCC|[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00016/978-1-78801-789-3)| |
AITD-02356|Maximum Likelihood Methods|最大似然法| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00109/978-1-78801-789-3)|统计|
AITD-02357|Maximum Likelihood Procedures|最大似然估计法| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00311/978-1-78801-789-3)|统计|
AITD-02358|MCTS Method|蒙特卡洛树搜索方法| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00136/978-1-78801-789-3)| |
AITD-02359|Mean-Squared Error|均方误差| |[[1]](https://www.nature.com/articles/s41557-021-00716-z)|统计、机器学习|
AITD-02360|Mechanical Sympathy|机械同感，软硬件协同编程| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00109/978-1-78801-789-3)| |
AITD-02361|Merging|合并| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00311/978-1-78801-789-3)| |
AITD-02362|Message Passing Neural Networks|消息传递神经网络|MPNNS|[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00372/978-1-78801-789-3)| |
AITD-02363|Microarray Data|微阵列数据| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00206/978-1-83916-023-3)| |
AITD-02364|Mini Batch|小批次| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00076/978-1-78801-789-3)| |
AITD-02365|Mining|挖掘| |[[1]](https://www.nature.com/articles/s41557-021-00716-z)| |
AITD-02366|Mining Out|挖掘| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00037/978-1-78801-789-3)| |
AITD-02367|Missing Values|缺失值| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00311/978-1-78801-789-3)|统计|
AITD-02368|ML Algorithm|机器学习算法| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00016/978-1-78801-789-3)| |
AITD-02369|ML Modelling|机器学习建模| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00206/978-1-83916-023-3)| |
AITD-02370|ML Potentials|机器学习势能| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00076/978-1-78801-789-3)| |
AITD-02371|ML-Driven|机器学习驱动的| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00136/978-1-78801-789-3)| |
AITD-02372|ML-Driven Optimization|机器学习驱动的最优化| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00136/978-1-78801-789-3)| |
AITD-02373|MLP Neural Model|多层感知机神经模型| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00227/978-1-78801-789-3)| |
AITD-02374|Model Construction|模型构建| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00311/978-1-78801-789-3)| |
AITD-02375|Model Evaluation|模型评估| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00311/978-1-78801-789-3)| |
AITD-02376|Model Performance|模型性能| |[[1]](https://www.nature.com/articles/s41557-021-00716-z)| |
AITD-02377|Model Statistics|模型统计| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00037/978-1-78801-789-3)| |
AITD-02378|Model Training|模型训练| |[[1]](https://www.nature.com/articles/s41557-021-00716-z)|机器学习|
AITD-02379|Model Validation|模型验证| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00016/978-1-78801-789-3)| |
AITD-02380|Model-Based Iterative Reconstruction|基于模型的迭代重建|MBIR|[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00450/978-1-78801-789-3)| |
AITD-02381|Model-Construction|模型构建| |[[1]](https://www.nature.com/articles/s41557-021-00716-z)| |
AITD-02382|Modelling Scenario|建模场景| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00016/978-1-78801-789-3)| |
AITD-02383|Molecular Graph Theory|分子图论| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00037/978-1-78801-789-3)| |
AITD-02384|Molecular Modelling|分子建模| |[[1]](https://www.nature.com/articles/s41557-021-00716-z)| |
AITD-02385|Monte Carlo Tree Search|蒙特卡洛树搜索|MCTS|[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00136/978-1-78801-789-3)[[2]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00169/978-1-78801-789-3)[[3]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00280/978-1-78801-789-3)|数学|
AITD-02386|Moore’S Law|摩尔定律| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00512/978-1-78801-789-3)|计算机|
AITD-02388|Multi-Agent Control System|多智能体控制系统| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00340/978-1-78801-789-3)| |
AITD-02389|Multi-Core Desktop Computer|多核台式计算机| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00136/978-1-78801-789-3)|计算机|
AITD-02390|Multi-Dimensional Big Data Analysis|多维度大数据分析| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00424/978-1-78801-789-3)| |
AITD-02391|Multi-Layer Feed-Forward|多层前馈|MLFF|[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00076/978-1-78801-789-3)| |
AITD-02392|Multi-Objective Genetic Algorithm|多目标遗传算法|MOGA|[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00311/978-1-78801-789-3)| |
AITD-02393|Multi-Objective Optimization|多目标优化| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00227/978-1-78801-789-3)|机器学习|
AITD-02394|Multi-Reaction Synthesis|多反应合成| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00136/978-1-78801-789-3)| |
AITD-02395|Multilayer Perceptron|多层感知机| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00227/978-1-78801-789-3)| |
AITD-02396|Multivariate Regression|多变量回归| |[[1]](https://pubs.rsc.org/en/content/chapter/bk9781788017893-00037/978-1-78801-789-3)| |
