在MathWorks官方网站中,导航到“Products”部分,然后找到“Statistics and Machine Learning Toolbox”。 下载安装包: 在Statistics and Machine Learning Toolbox的产品页面,点击“Download”按钮,选择合适的MATLAB版本和操作系统平台,下载对应的安装包。 执行安装步骤: 打开MATLAB软件。 在MATLAB的命令窗口中输入以下命令...
相应的，在Statistics and Machine Learning Toolbox中提供用于执行受监督和无/非监督机器学习的方法。分类算法使用户可以将一个分类应变量建模为一个或多个预测元的函数。Statistics and Machine Learning Toolbox提供涵盖多种参数化和非参数化分类算法的应用程序和函数，如logistic回归、朴素贝叶斯、k近邻、SVM等。分类...
Statistics and Machine Learning Toolbox 提供了一系列函数和 App,可用于数据描述、分析和建模。您可以使用描述性统计量、可视化和聚类进行探索性数据分析;对数据进行概率分布拟合;生成用于蒙特卡罗模拟的随机数,以及执行假设检验。借助工具箱提供的回归和分类算法,您可以基于数据进行推断并构建预测模型;您既可选择分类学习...
Statistics and Machine Learning Toolbox™ provides functions and apps to describe, analyze, and model data. You can use descriptive statistics, visualizations, and clustering for exploratory data analysis, fit probability distributions to data, generate random numbers for Monte Carlo simulations, and ...
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Statistics and Machine Learning Toolbox provides functions and apps to describe, analyze, and model data using statistics and machine learning.
Statistics and Machine Learning Toolbox™ provides tools for accessing, preprocessing, and visualizing data; extracting features; training and optimizing models; and preparing models for deployment. The typical workflow begins with accessing, cleaning, and preprocessing your data in preparation for extract...
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Machine learning uses two types of techniques: supervised learning, which trains a model on known input and output data so that it can predict future outputs, and unsupervised learning, which finds hidden patterns or intrinsic structures in input data. ...