深入机器学习系列之：FactorAnalysis

来源： 星环科技

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新增用户数+老用户数=活跃用户数

An extension of principal component analysis(PCA) in the sense of approximating covariance matrix.

Goal

To describe the covariance relationships among many variables in terms of a few underlying unobservable random variables, called factors.

To reduce dimensions and solve the problem with n<p.

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Orthogonal Factor Model（正交因子模型）

A Factor Analysis Example

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Estimation

3.1 Principal Component Method

3.2 Maximum Likelihood Method

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Factor Rotation

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Factor Scores