How to identify critical parameters in a dataset?

mzn

Hi,
Say that you have a dataset of 10 different parameters (listed in 10 columns) to describe a phenomenon (listed in the 11 column). What would be a procedure to identify which of the 10 parameters are critical to predicting the phenomenon on hand (i.e. maybe 4-5 parameters are need to properly predict the phenomenon, how to go around figuring out what are these parameters?).
Thanks, 

varunm1

Hi @mzn

Auto model will provide you with attributes (Parameters) that support the prediction. If you don't have access to automodel, you can also see the correlation of these attributes to output using the correlation matrix operator. You can look at some feature selection technique operators like optimize selection, forward selection

If you are trying to predict using different algorithms like a decision tree, SVM, etc., you can use explain predictions operator to see which attributes are helpful in predictions for a particular algorithm

 Thanks