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Preprocessing ahead of Predictor Screening analysis

Hello,

I have some characterisation data that I would like to subject to predictor screening. The variables are on different scales. Is any preprocessing like standardisation required prior to the predictor screening?

Predictive Modeling and Machine Learning

Re: Preprocessing ahead of Predictor Screening analysis

Tree methods, like predictor screening, partition, bootstrap forest, and boosted trees (and XGBoost) don't need pre processing. They work well on dirty data too (missing, outliers, strong X correlation with Y...

Re: Preprocessing ahead of Predictor Screening analysis

Hi @kjwx109,

As @Byron_JMP mentioned, the Predictor Screening platform is based on a Random Forest, which is a tree-based method robust to outliers, collinearity between variables, scales of the variables...
You can find more infos here : Predictor Screening

If you need further infos or if you have more questions, don't hesitate

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