Hi everyone, I wonder if you could provide me with some suggestions on how to determine the confidence and prediction intervals of SVR? If you have suggestions for any machine learning algorithms in general, that would be fine too (doesn't have to be specific for SVR).
So far, I have found: 1. Bootstrap: http://stats.stackexchange.com/questions/183230/bootstrapping-confidence-interval-from-a-regression-prediction 2. http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0048723&type=printable 3. ftp://ftp.esat.kuleuven.ac.be/sista/suykens/reports/10_156_v0.pdf But, I don't fully understand the details in #2 and #3 to the point that I can write a step by step code. If I use bootstrap method, I can get the confidence interval as follows? a. Draw bootstrap sample of size n b. Fit the SVR model (with hyperparameters chosen during model selection with grid search cv) to this bootstrap sample c. Use this model to predict the output variable y* from input variable X* d. Repeat step a-c for, for instance, 100 times e. Order the 100 values of y*, and determine, for instance, the 10th percentile and 90th percentile (if we are looking for 0.8 confidence interval) f. Repeat a-e for different values of X* to plot the prediction with confidence interval But, I don't know how to get the prediction interval from here. Thank you very much, Raga
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