Comments by Member 10305598

Member 10305598 4-Nov-13 8:25am View

I have tried both the ways, the predicted labels are same for the test data.
LIBSVM read-me file describes the function like this -Function: void svm_cross_validation(const struct svm_problem *prob,
const struct svm_parameter *param, int nr_fold, double *target);

This function conducts cross validation. Data are separated to
nr_fold folds. Under given parameters, sequentially each fold is
validated using the model from training the remaining. Predicted
labels (of all prob's instances) in the validation process are
stored in the array called target.
Is there any difference when I pass the model returned by svm_train to the cross-validation method?

Member 10305598 29-Oct-13 22:40pm View

Thanks for the answer! Is the LIBSVM setup code(the node and model)fine?

Member 10305598 28-Oct-13 22:35pm View

I re-checked the weight vector values using quadprog in matlab and the values are similar to the matlab code using dll files

Member 10305598 15-Oct-13 11:49am View

I built the function based on Random and my question was - is my implementation correct in Java. Since I am new to Java I am reading documents/notes and then trying to implement as I learn.

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