Feature Selection from Mixed dataset
Kind of a cop out but you could simply use a random forest and happily mix numerical and categorical data.  Encoding with LabelEncoder on OneHotEncoding would allow you to use a wider variety of algorithms.
I am a newbie in data science domain.
I have a data set, which has both numerical and string data.The interesting fact is both type of data make sense for the outcome. How to choose the relevant features from the data set?
Should I be using the LabelEncoder and convert the data from string to numerical and continue with the correlation? I am taking the right path? Is there any better way to solve this crisis?