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I'm using 5 algorithms for machine learning analysis of my data, (coxph, coxtime, rfsrc, deephit, deepsurv)
My dataset contains 40 features and 1700 observations.
I used nested cross-validation (inner folds = 10, outer folds = 3) and benchmarking for optimizing hyperparameters and comparing algorithms accuracy.
Hyperparameters to be optimized included number of nodes of layers, epochs, dropout, alpha for neural network, and mtry, nodesize for rfsrc.
I used random_search method.
For termination rule, I've chosen 60 iteration.
I have started analysis at 9:00 am and now it is 2:00pm, but my computer is still analysing.
my OS is windows 10, CPU intel corei7 8550U 1.8-1.99 GHz, RAM 12GB.
I'm using R 4.0.3 and mlr3proba package.
Is it normal for machine learning analysis to last many hours?
Honestly I have read in literature that it may takes for hours, but I don't know does it apply for complexity of my analysis? or there is a problem ?

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    $\begingroup$ I advise you to log your program's progress. O/w no one can precisely answer your question. But, it seems you've 60 x 10 x 3 x 5 = 9K combinations to try out. Roughly, in ~5 hours, that means 30 combinations to try in a minute (one comb in 2 sec). Was that possible in your trials with your setup? $\endgroup$
    – gunes
    Apr 19, 2021 at 9:40
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    $\begingroup$ Thanks, According to your calculation and my setup experience, I think no, it is not possible to perform one comb in 2 second. so I think I should wait more. Because the same parameters analysis but with much lower iterations were all successful before. And also in the future I should log my progress before starting time demanding analysis. $\endgroup$ Apr 19, 2021 at 10:48

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