Principal Component Analysis

• Category: Machine Learning
• Development language: Python 2.7
• Operating platform / Operating system: windows
• Compilation tools and environment: Spyder
• GitHub download path: https://github.com/Three-Poles/Machine-learning

Method description:

Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components.

Installation: online;

Dependent libraries: sklearn;

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• 依赖库文件：sklearn

  安装方式：在线安装

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