I have a confusion to decide which feature selection method that I should employ in my research whose objective is to analyze which features that are significant in representing a certain condition of the human body, lie on two categories: normal or not.
I used multiple sensors to determine some features and plan to characterize the signal through the feature respecting the patient condition.
I have explored so many articles and blog about the fittest method for doing feature selection in classifying data into two categories. and this one is pretty good to me:
It said that we can use ANOVA and kendall's rank,
but on another site, it is mentioned that RFE could be employed too in selecting features for classifying data, another paper also said that we could employ mRmR, genetic algorithm, and Relief,
I am not sure about this, but is it mean I can employ all of those on feature selection without any further restriction according to my research objective?