Timeline for Using SVM and Logistic Regression for survival analysis
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
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| Jul 2, 2018 at 13:59 | comment | added | bawa | I would be happy to discuss this over a real-time chat or something if possible. | |
| Jul 2, 2018 at 13:58 | comment | added | bawa | Yes this would be supervised. I dont believe I have time-varying covariates (if i understand correctly). Apologies, I am still a bit new to survival analysis. I have an online retail data which makes it tricky to tell if they have churned or not. The data: archive.ics.uci.edu/ml/datasets/online+retail I am not sure how I can build a model that gives me different predictions for 30 and 60 days. This is what my question is really. I have reduced the data into RFM (Recency, Frequency, Monetary) variables. I would like to build a model to give different predictions for 30 and 60 days | |
| Jul 2, 2018 at 13:45 | comment | added | hlsmith | @bawa - So would this be supervised, in that you are creating a model with a known outcome? I wonder if you could add days into your model and extrapolate out into the future by adjusting the time value. Do you have time-varying covariates. This is a unique phenomenon that takes particular consideration not to open backdoor paths between the outcome and the exposures. Can you post what you think your current model may look like along with what data you do have. This can help other better direct their suggestions. | |
| Jul 2, 2018 at 13:17 | comment | added | bawa | You are correct, I am trying to predict at a set point (in 30 days, 60 days). I was wondering how can I do this though? How do I set it so SVM or Logistic Regression give me predictions in 30/60 days time? | |
| Jul 2, 2018 at 13:08 | history | edited | hlsmith | CC BY-SA 4.0 |
added 257 characters in body
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| Jul 2, 2018 at 13:02 | history | answered | hlsmith | CC BY-SA 4.0 |