I’m focusing on a private project of prediction in 1vs1 sports activities. My neural network (MLP) have an precision of 65% (not great nonetheless it’s an excellent start). I have 28 options and I believe that some affect my predictions. So I used two algorithms mentionned in your article :
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On this area from the Python class, find out how to utilize Python and control stream so as to add logic for your Python scripts!
I did examination each case but benefits are different, exemple (first case column A and B are very important but next circumstance column C and D are very important)
Can i use linear correlation coefficient among categorical and constant variable for element choice.
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what to do with correlated features? should really We modify them to a little something new? a mixture maybe? So how exactly does it have an affect on our modeling and prediction? appreciated in the event you immediate me into some resources to review and discover it out.
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Are it depend on the check precision of product?. In other indicating exactly what is the difference between extract attribute soon after prepare just one epoch or teach one hundred epoch? what is greatest functions?, may very well be my dilemma foolish but i need response for it.