Hyperparameter Optimization for a Machine Learning Algorithm
You are right, what has to be changed is the objective. You are currently using accuracy as a measure of how good your classifier is. Accuracy is not a good measure when you have class imbalance. For this reason, other objectives have to be used. AUC is a better measure, and so is the log-loss, although not that interpretable. However, both AUC and log-loss need you method to output probabilities, not just predictions of classes. For this reason, it is required that your SVM implementation has a predict probability method.