Tackling a high-dimensional dataset can be challenging in machine learning. How would you approach the problem?

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Anonymous · Accepted Answer

From the data, I need to know how research questions could be extracted from a
high-dimensional dataset. Once which model should be used is decided, then I
feed the dataset into the machine learning model. The problem is that in a
high-dimensional dataset, the number of samples is smaller than the predictors,
the control variables. It is important to drop the unrelated variables, and make
sure the model predicts well with the given dataset.

Tackling a high-dimensional dataset can be challenging in machine learning. How would you approach the problem?

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