I trained a SVM model for binary classification use case. Dataset had 25 variables and 100 observations.
Accuracy, Precision and Recall output were not satisfactory with 0.60, 0.38 and 0.55 respectively which is tad too low.
I have been reading articles on SVM articles and understand that its performance is much better on high dimension datasets and lower observations. Works best for Non linear type of problems
Is that the reason for it not to work optimally for the specified use case ?
I chose kernel as Linear, C=1 and Gamma = 10
Any suggestions on this will be highly appreciated