Linked Questions
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Why do PCA scores in a regression lead to higher accuracy than raw variables?
I have a dataset that has some 25 continuous variables and a continuous target. A tutor showed using this dataset, that when PCA scores are used instead of raw variables as inputs for predicting ...
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How to interpret PCA loading and to relate it with correlation coefficient of associated independent variable with dependent variable
There are 2 sides to this question. On the first side, we are trying to run PCA.
While running PCA on a dataset having 62 independent variables (IVs), I have found that first component (PC1) explains ...
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How can a later principal component be significant predictor in a regression, when an earlier PC is not? [duplicate]
I have a question regarding principal component regression (regression of a DV on principal components). I have 4 components in my PCR and the third component is non-significant as a predictor. What ...
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Reference for this claim: important features in data can be "hidden" in the higher PCA axes that are typically thrown out [duplicate]
I remember reading a paper a while ago that demonstrated some cases in which PCA would fail to capture important features of a data set in the first few principal components, but where those features ...
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Example datasets where PCA could improve or decrease performance of SVM? [duplicate]
Going through the top answers in How can top principal components retain the predictive power on a dependent variable (or even lead to better predictions)?, I understand that doing PCA and keeping the ...
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