CODEWITHSUNDEEP
rmachine-learningmlr
User12547645
User12547645

Reputation: 8437

How to predict the brier score for a cox regression?

I am using the mlr package to do machine learning in R. I am using a the cvcoxboost algorithmn on a dataset and would like to calculate the brier score of the output.

This should work, since listMeasures(cvcoxboost.tsk) also lists the measurement ibrier. The entire code looks like this: 

cvcoxboost.lrn = makeLearner("surv.cv.CoxBoost") 
cvcoxboost.tsk = makeSurvTask(data = data, target = c("time", "event"))
cvcoxboost.mod = train(cvcoxboost.lrn, cvcoxboost.tsk, subset = data.train) 
cvcoxboost.tsk.pred = predict(cvcoxboost.mod, task = cvcoxboost.tsk, subset = data.test)

listMeasures(cvcoxboost.tsk) # "iauc.uno" "featperc"    "ibrier"      "timeboth"  "timetrain"   "timepredict" "cindex.uno"  "cindex"  

performance(cvcoxboost.tsk.pred, measures = mlr::cindex)
performance(cvcoxboost.tsk.pred, measures = cindex.uno, model = cvcoxboost.mod, task = cvcoxboost.tsk)
performance(cvcoxboost.tsk.pred, measures = mlr::ibrier, model = cvcoxboost.mod, task = cvcoxboost.tsk)

...and I receive the error No method for evaluating predicted probabilities from objects in class: CoxBoost.

Upvotes: 0

Views: 741

Answers (1)

PhilippPro
PhilippPro

Reputation: 698

ibrier only works for certain learners that are supported by the pec package like randomForestSRC or cox. This is currently not well documented enough, but you can look into the pec package to see which models are supported.

Upvotes: 2

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