i have a small question regarding optimising the parameters for a model.
i would like to know is there any way the model can check the range of values for a specific parameters and give me the result based on that.
For example in titanic data set we have age column and class (lower ,middle,upper),i fix the age range from 20 to 30 and fix the class value as lower ,i would like the see which age group from 20 to 30 in lower desk has high possibility of survival.
Is there a way i can optimise the model for the above case?
HI Thomas ,
What i am looking is little different ,here i can only change the options for the operators in the model like no of trees or maximum depth , but i want to change the data in the attribute.i want to see like in titanic data set for age between 20 to 40 at what age the people has the highest survival rate so by fixing the age between 20 to 40 and i want see the parameters with highest survual rate.
I came across this kind of feature in Mando Brain Augumeneted intelligence tool ,so i am wondering is there NY similar kind of options in rapidminer.In model simulator i can only fix the all the values and see the result, but not like fixing some attribute the values and changing the range of attribute values .
Training a logistic regression model could help you analyze which features impact more upon the survival and even compare the relative risks of different realizations of the variables. It kind of sucks for forecasting, but it's good for interpretation.