Why did Logistic regression perform better than svm?
There is a theorem in machine learning literature which is called “No free lunch theorem”. The essence of NFL is that there is no universal model which performs best for every problem and every dataset. So, according to NFL, you can not expect SVM to outperferm logistic regression in all situations and contexts. If your classes were linearly separable SVM would be perfect with 100% accuracy but otherwise you shouldn’t expect it to necessarily outperform ligistic regression. So, whether SVM or ligistic regression are better choice highly depends on the problem and on the available dataset.