Using the SPSS APRIORI INC command is it possible to then assign a
value (yes/no 1/0) for those cases that meet the "rule" in the classification table created in the output. Peter Sent from my iPhone ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
You will have many rules in the output
table, so this question could mean several things including:
- create an indicator variable for each rule indicating whether a case meets it - create an indicator variable for each rule meeting some support and confidence thresholds and create indicator variables for those - select a particular consequent and calculate on the estimation or new data which cases meet it. In order to do something like this, you would capture the table with OMS parse the rules column and generate the requisite transformation. This would be most easily done with a little Python code. If you would spell out the actual task, I can help with that. Jon Peck (no "h") aka Kim Senior Software Engineer, IBM [hidden email] phone: 720-342-5621 From: Peter Spangler <[hidden email]> To: [hidden email], Date: 08/23/2013 10:51 PM Subject: [SPSSX-L] CLASSIFICATION Sent by: "SPSSX(r) Discussion" <[hidden email]> Using the SPSS APRIORI INC command is it possible to then assign a value (yes/no 1/0) for those cases that meet the "rule" in the classification table created in the output. Peter Sent from my iPhone ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
create an indicator variable for each rule meeting some support and confidence thresholds and create indicator variables for thoseYES, I would like to create indicator variables where Rule A: {popcorn, movie}=>{beer} with support .01 and confidence .40 - select a particular consequent and calculate on the estimation or new data which cases meet it.YES, estimate which new cases will meet Rule A. Using the Python module sounds like a great implementation resource as well! Sent from my iPhone
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