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How to split data using cross validation on Spark for SVM and DT
I use Spark MLlib for my project. I have used SVM, Decision Tree and Random Forest. I have split the dataset into Training and Testing (60% training, 40 % testing) and got my results.
I want to repeat my work but splitting the data using Cross Validation instead of percentage split for SVM, DT and RF.
How can I do that on Spark?
I have found several codes for splitting using logistic regression and Pipeline whcih can not work for SVM.
I need to split the data int 10 fold, then apply SVM for now.
also I want to print the Accuracy for each fold.
apache-spark svm cross-validation
asked Jan 1 at 6:01
user3069106user3069106
11
add a comment |
I use Spark MLlib for my project. I have used SVM, Decision Tree and Random Forest. I have split the dataset into Training and Testing (60% training, 40 % testing) and got my results.
I want to repeat my work but splitting the data using Cross Validation instead of percentage split for SVM, DT and RF.
How can I do that on Spark?
I have found several codes for splitting using logistic regression and Pipeline whcih can not work for SVM.
I need to split the data int 10 fold, then apply SVM for now.
also I want to print the Accuracy for each fold.
apache-spark svm cross-validation
asked Jan 1 at 6:01
user3069106user3069106
11
Did you check this answer stackoverflow.com/questions/32769573/…?
– Moustafa Mahmoud
Jan 3 at 11:44
Thanks. This example and lot of examples I've seen using Pipeline which work for Decision tree and RF. But not for SVM. How can I do cross validation for SVM?
– user3069106
Jan 6 at 7:02
add a comment |
I use Spark MLlib for my project. I have used SVM, Decision Tree and Random Forest. I have split the dataset into Training and Testing (60% training, 40 % testing) and got my results.
I want to repeat my work but splitting the data using Cross Validation instead of percentage split for SVM, DT and RF.
How can I do that on Spark?
I have found several codes for splitting using logistic regression and Pipeline whcih can not work for SVM.
I need to split the data int 10 fold, then apply SVM for now.
also I want to print the Accuracy for each fold.
apache-spark svm cross-validation
asked Jan 1 at 6:01
user3069106user3069106
11
I use Spark MLlib for my project. I have used SVM, Decision Tree and Random Forest. I have split the dataset into Training and Testing (60% training, 40 % testing) and got my results.
I want to repeat my work but splitting the data using Cross Validation instead of percentage split for SVM, DT and RF.
How can I do that on Spark?
I have found several codes for splitting using logistic regression and Pipeline whcih can not work for SVM.
I need to split the data int 10 fold, then apply SVM for now.
also I want to print the Accuracy for each fold.
apache-spark svm cross-validation
apache-spark svm cross-validation
asked Jan 1 at 6:01
user3069106user3069106
11
asked Jan 1 at 6:01
user3069106user3069106
11
edited Jan 3 at 10:09
user3069106
asked Jan 1 at 6:01
user3069106user3069106
11
asked Jan 1 at 6:01
user3069106user3069106
11
asked Jan 1 at 6:01
user3069106user3069106
11
11
Did you check this answer stackoverflow.com/questions/32769573/…?
– Moustafa Mahmoud
Jan 3 at 11:44
Thanks. This example and lot of examples I've seen using Pipeline which work for Decision tree and RF. But not for SVM. How can I do cross validation for SVM?
– user3069106
Jan 6 at 7:02
add a comment |
Did you check this answer stackoverflow.com/questions/32769573/…?
– Moustafa Mahmoud
Jan 3 at 11:44
Thanks. This example and lot of examples I've seen using Pipeline which work for Decision tree and RF. But not for SVM. How can I do cross validation for SVM?
– user3069106
Jan 6 at 7:02
Did you check this answer stackoverflow.com/questions/32769573/…?
– Moustafa Mahmoud
Jan 3 at 11:44
Did you check this answer stackoverflow.com/questions/32769573/…?
– Moustafa Mahmoud
Jan 3 at 11:44
Thanks. This example and lot of examples I've seen using Pipeline which work for Decision tree and RF. But not for SVM. How can I do cross validation for SVM?
– user3069106
Jan 6 at 7:02
Thanks. This example and lot of examples I've seen using Pipeline which work for Decision tree and RF. But not for SVM. How can I do cross validation for SVM?
– user3069106
Jan 6 at 7:02
add a comment |
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Did you check this answer stackoverflow.com/questions/32769573/…?
– Moustafa Mahmoud
Jan 3 at 11:44
Thanks. This example and lot of examples I've seen using Pipeline which work for Decision tree and RF. But not for SVM. How can I do cross validation for SVM?
– user3069106
Jan 6 at 7:02