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Using Predefined Splits in PCR function R PLS package
Grouping functions (tapply, by, aggregate) and the *apply family100% accuracy from libsvmCompute Random Forest with a leave one ID out cross validationGrouping rows from an R dataframe together when randomly assigning to training/testing datasetsHow to apply classifier from one set to another in weka & graph training/testing errornumpy: How can I select specific indexes in an np array for k-fold cross validation?Splitting multi-tier data into 5 folds using pythonsklearn Group K-fold and groups parameters in other cross-validators similarityUsing Scikit-Learn GridSearchCV for cross validation with PredefinedSplit - Suspiciously good cross validation resultsUse train package for cross validation taking forever in R
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
In order to to ensure a good population representation I have created custom validation sets from my training data. However, I am not sure how I interface this in PCR in R
I have tried to add a list in the segments argument with each index similar to what you do in python predefined splits cv iterator, which runs but takes forever. So I feel I must be making an error somewhere
pcr(y~X,scale=FALSE,data=tdata,validation="CV",segments=test_fold)
where test fold is a list containing the validation set which belongs in the index
For example if the training data is composed on 9 samples and I want to use the first three as the first validation set on son
test_fold<-c(1,1,1,2,2,2,3,3,3)
This runs but it is very slow where if I do regular "CV" it runs in minutes. So far the results look okay but I have a over a thousand runs I need to do and it took 1 hr to get through one. So if anybody knows how I can speed this up I would be grateful.
r cross-validation pls
asked Mar 27 at 18:54
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
add a comment |
In order to to ensure a good population representation I have created custom validation sets from my training data. However, I am not sure how I interface this in PCR in R
I have tried to add a list in the segments argument with each index similar to what you do in python predefined splits cv iterator, which runs but takes forever. So I feel I must be making an error somewhere
pcr(y~X,scale=FALSE,data=tdata,validation="CV",segments=test_fold)
where test fold is a list containing the validation set which belongs in the index
For example if the training data is composed on 9 samples and I want to use the first three as the first validation set on son
test_fold<-c(1,1,1,2,2,2,3,3,3)
This runs but it is very slow where if I do regular "CV" it runs in minutes. So far the results look okay but I have a over a thousand runs I need to do and it took 1 hr to get through one. So if anybody knows how I can speed this up I would be grateful.
r cross-validation pls
asked Mar 27 at 18:54
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
add a comment |
In order to to ensure a good population representation I have created custom validation sets from my training data. However, I am not sure how I interface this in PCR in R
I have tried to add a list in the segments argument with each index similar to what you do in python predefined splits cv iterator, which runs but takes forever. So I feel I must be making an error somewhere
pcr(y~X,scale=FALSE,data=tdata,validation="CV",segments=test_fold)
where test fold is a list containing the validation set which belongs in the index
For example if the training data is composed on 9 samples and I want to use the first three as the first validation set on son
test_fold<-c(1,1,1,2,2,2,3,3,3)
This runs but it is very slow where if I do regular "CV" it runs in minutes. So far the results look okay but I have a over a thousand runs I need to do and it took 1 hr to get through one. So if anybody knows how I can speed this up I would be grateful.
r cross-validation pls
asked Mar 27 at 18:54
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
In order to to ensure a good population representation I have created custom validation sets from my training data. However, I am not sure how I interface this in PCR in R
I have tried to add a list in the segments argument with each index similar to what you do in python predefined splits cv iterator, which runs but takes forever. So I feel I must be making an error somewhere
pcr(y~X,scale=FALSE,data=tdata,validation="CV",segments=test_fold)
where test fold is a list containing the validation set which belongs in the index
For example if the training data is composed on 9 samples and I want to use the first three as the first validation set on son
test_fold<-c(1,1,1,2,2,2,3,3,3)
This runs but it is very slow where if I do regular "CV" it runs in minutes. So far the results look okay but I have a over a thousand runs I need to do and it took 1 hr to get through one. So if anybody knows how I can speed this up I would be grateful.
r cross-validation pls
r cross-validation pls
asked Mar 27 at 18:54
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
asked Mar 27 at 18:54
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
asked Mar 27 at 18:54
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
asked Mar 27 at 18:54
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
asked Mar 27 at 18:54
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
561 silver badge9 bronze badges
add a comment |
add a comment |
1 Answer
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So the segments parameters needs to be a list of multiple vectors. So going again with 9 samples if I want the first three to be in the first validation set, the next three in the second validation set and so on it should be
test_vec<-list(c(1,2,3),c(4,5,6),c(7,8,9))
answered Mar 27 at 20:39
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
add a comment |
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So the segments parameters needs to be a list of multiple vectors. So going again with 9 samples if I want the first three to be in the first validation set, the next three in the second validation set and so on it should be
test_vec<-list(c(1,2,3),c(4,5,6),c(7,8,9))
answered Mar 27 at 20:39
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
add a comment |
So the segments parameters needs to be a list of multiple vectors. So going again with 9 samples if I want the first three to be in the first validation set, the next three in the second validation set and so on it should be
test_vec<-list(c(1,2,3),c(4,5,6),c(7,8,9))
answered Mar 27 at 20:39
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
add a comment |
So the segments parameters needs to be a list of multiple vectors. So going again with 9 samples if I want the first three to be in the first validation set, the next three in the second validation set and so on it should be
test_vec<-list(c(1,2,3),c(4,5,6),c(7,8,9))
answered Mar 27 at 20:39
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
So the segments parameters needs to be a list of multiple vectors. So going again with 9 samples if I want the first three to be in the first validation set, the next three in the second validation set and so on it should be
test_vec<-list(c(1,2,3),c(4,5,6),c(7,8,9))
answered Mar 27 at 20:39
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
answered Mar 27 at 20:39
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
answered Mar 27 at 20:39
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
answered Mar 27 at 20:39
Joshua MannheimerJoshua Mannheimer
561 silver badge9 bronze badges
561 silver badge9 bronze badges
add a comment |
add a comment |
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