I've downloaded a data set from UCI Machine Learning Repository. In the description of the data set, they talk about "predictive attribute" and "non-predictive attribute". What does it mean and how can you identify them in a data set?
To me, it looks like attributes relates to type of data points available; therefore a predictive attribute would be a data point that can be used to "predict" something, such as MYCT
, MMIN
, MMAX
, CACH
, CHMIN
, CHMAX
. The "non-predictive attribute" would be the vendor names and model name. PRP seems to be the goal field, and linear regression guess is ERP.