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I did exam both circumstance but final results are diverse, exemple (1st case column A and B are crucial but second situation column C and D are essential)
That could be a good deal of new binary variables. Your resulting dataset is going to be sparse (many zeros). Feature selection prior may be a good idea, also consider just after.
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In predictive modeling we're concerned with growing the click here for info skill of predictions and lowering product complexity.
I've applied the extra tree classifier for that aspect choice then output is worth score for each attribute.
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