NIPALS 算法留1法 交叉检验绘图

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NIPALS 算法留1法 交叉检验绘图

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In the current text, the author briefly mentions the NIPALS algorithm, a method for estimating multivariate models. However, it would be useful to provide some additional information about the algorithm and how it works. For example, the NIPALS algorithm is an iterative process that seeks to identify the principal components of a matrix by successively approximating the matrix using orthogonal projections. Furthermore, the author mentions a "留1法" in relation to the NIPALS algorithm, which is likely a reference to the leave-one-out cross-validation technique. This technique involves systematically removing one observation from the dataset, estimating the model on the remaining observations, and then evaluating the performance of the model on the observation that was removed. Finally, the author mentions the creation of "交叉检验绘图" in relation to the NIPALS algorithm. It would be helpful to provide some additional context about what this graph represents and how it can be used to evaluate the performance of the NIPALS algorithm.