最新特性
了解最新 MATLAB 机器学习特性
交互式应用程序
- 使用 Classification Learner 应用程序交互式浏览数据、选择特征、训练与评估监督式分类模型
- 新特性 利用 Regression Learner应用程序交互式训练回归模型
- 使用 Distribution Fitter 应用程序让数据拟合于广泛的概率分布，并探索参数值变更的效果
Automated Model Optimization
- New Optimize model type and hyperparameters simultaneously
- Automatically tune hyperparameters using Bayesian optimization
- Automatically select a subset of relevant features using techniques like neighborhood component analysis (NCA) and feature ranking
- Parallelize the execution of automated optimization methods on multiple cores using Parallel Computing Toolbox, and scale to clouds and clusters using MATLAB Parallel Server
Related Products: MATLAB Parallel Server, Parallel Computing Toolbox, Statistics and Machine Learning Toolbox
Machine Learning and Statistical Algorithms
- Leverage commonly used algorithms for classification and regression, such as linear and generalized linear models, support vector machines, decision trees, ensemble methods, and more
- Use popular clustering algorithms including k-means, k-mediods, hierarchical clustering, Gaussian mixture, and Hidden Markov models
- New Use density-based spatial clustering of applications with noise (DBSCAN) and spectral clustering of arbitrary shapes
- Run statistical and machine learning computations faster than with open-source tools
Related Products: Statistics and Machine Learning Toolbox
Data Visualization
- Explore the structure of your data and relationships between features through scatter plots, box plots, dendrograms, and other standard statistical visualizations
- Use advanced dimensionality reduction algorithms like Stochastic Neighbor Embedding (t-SNE)
- Visualize high-density data with improved scatter plots in the Classification Learner app
- New Create confusion matrices from tall arrays
Related Products: Statistics and Machine Learning Toolbox
Deployment
- Automatically generate C/C++ code for many popular classification, regression, and clustering algorithms
- New Deploy to devices with limited memory and/or power using fixed-point arithmetic
- New Update parameters of deployed models such as SVM, linear models, and decision trees, without regenerating C/C++ prediction code
Related Products: MATLAB Coder, MATLAB Compiler, Statistics and Machine Learning Toolbox
大数据
- 将 tall 数组与许多分类、回归和聚类算法结合使用，在无法存入内存的数据集上训练模型
- 通过延迟处理完整数据集，最大限度地减少潜在问题
- 新特性 将核心 SVM 回归和分类模型拟合与 tall 数组结合使用
- 新特性 在超出内存的数据上应用快速近似均值、分位数和非分层分区
相关产品: Parallel Computing Toolbox, Statistics and Machine Learning Toolbox
部署
- 为诸多常用的分类、回归和聚类算法自动生成 C/C++ 代码
- 新特性 通过使用 k-最近邻和非树型集成模型，生成用于向量和矩阵距离计算以及预测的 C 代码
相关产品: MATLAB Coder, MATLAB Compiler, Statistics and Machine Learning Toolbox
获取免费试用版
30 天探索触手可及。
