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Multicollinearity in PLS1 Modeling Leads to Unexplainable Results.

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Multicollinearity in independent variables can mess up regular regression, but PLS Regression fixes that. PLSR lets you model even with lots of variables or small sample sizes. Some think you don't need to worry about variable selection with PLS Regression, but that's not true for PLS1 models. If you don't pick your variables carefully, your regression results might not make sense.