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I have a dataset which includes both equally categorical and numerical attributes. Ought to I do feature choice just before a single-very hot encoding of categorical capabilities or after that ?
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That is definitely just what I necessarily mean. I believe that the ideal features can be preg, pedi and age from the state of affairs beneath
Most certainly, there is absolutely no one very best list of capabilities for your difficulty. There are lots of with various skill/functionality. Locate a set or ensemble of sets that actually works finest for your requirements.
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 up vote 2 down vote Here's One more viewpoint
-For the construction with the model I was intending to use MLP NN, using a gridsearch to improve the parameters.
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Let’s check out three illustrations to provide you with a snapshot of the outcomes that LSTMs are capable of accomplishing.
All things considered, the capabilities reduction technics which embedded in some algos (like the weights optimization with gradient descent) supply some solution into the correlations challenge.
Statistical tests can be employed to choose All those capabilities that have the strongest connection Together with the output variable.