OV crashes when using “Classifier trainer” box with SVM classifier
Posted: Sat Jan 01, 2022 2:05 pm
Good Morning and happy new year !
I am using OV version 3.1.0 and I want to use a SVM classifier with a linear kernel to classify Task vs Rest condition with 2 features and ~20 observations per condition, in a custom scenario. However, when I use the "Classifier trainer" box with 10 or 5 times cross validation, when it starts performing the classification, OV sends a warning message "k-fold test may take a long time, be patient" and then crashes, closing.
I also tried to use the "Classifier trainer" box of OV version 2.2.0 which allows to set all classification parameters such as the kernel, OV does the classification but the classification performance and the confusion matrix are weird (cross-validation test accuracy: 37% and training set accuracy: 52%). Also, using a LDA classifier with both the versions of the box manages to achieve 80% accuracy.
Has anyone succeeded in using and getting good classification performances with the SVM on OV? Are there any special requirements for input features when using the SVM classifier?
Best wishes.
I am using OV version 3.1.0 and I want to use a SVM classifier with a linear kernel to classify Task vs Rest condition with 2 features and ~20 observations per condition, in a custom scenario. However, when I use the "Classifier trainer" box with 10 or 5 times cross validation, when it starts performing the classification, OV sends a warning message "k-fold test may take a long time, be patient" and then crashes, closing.
I also tried to use the "Classifier trainer" box of OV version 2.2.0 which allows to set all classification parameters such as the kernel, OV does the classification but the classification performance and the confusion matrix are weird (cross-validation test accuracy: 37% and training set accuracy: 52%). Also, using a LDA classifier with both the versions of the box manages to achieve 80% accuracy.
Has anyone succeeded in using and getting good classification performances with the SVM on OV? Are there any special requirements for input features when using the SVM classifier?
Best wishes.