Dear Colleagues
I hope all is well.
I am interested in doing penalized cox regression using PYTHON.
I came across the following way to do penalized cox regression:
Penalized Cox Models — scikit-survival 0.17.1
The code blocks 10 till 13 are doing the following:
Choosing the penalty strength alpha by :calculating the best value of penalty strength among all the values of penalty strength (alpha) by reducing the value by 1% in each iteration
then it perform 5 fold cross-validation to estimate the performance – in terms of concordance index – for each αα.
I am confused and dont fully understand the codeblock 13. I found that after codeblock 13, it executes the model that has the best alpha and calculate the coefficients. Is this right?
I wonder in codeblock 13, the how was the model executed? is it by doing gridsearch?
What is the name or type of this model? Is it elastic net regression?
Dear Hatem Ali ,
Cox’s proportional hazard’s model is often an appealing model, because its coefficients can be interpreted in terms of hazard ratio, which often provides valuable insight. However, if we want to estimate the coefficients of many features, the standard Cox model falls apart, because internally it tries to invert a matrix that becomes non-singular due to correlations among features.
https://scikit-survival.readthedocs.io/en/stable/user_guide/coxnet.html
Regards,
Shafagat
Hatem Ali
These links might be useful:
1. https://scikit-survival.readthedocs.io/en/stable/user_guide/coxnet.html
2. https://github.com/sebp/scikit-survival/issues/14
Following this links
https://cran.r-project.org/web/packages/glmnet/vignettes/Coxnet.pdf
https://scikit-survival.readthedocs.io/en/stable/user_guide/coxnet.html
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