I am trying to learn how to use the svm modeler e1071 in R. When I run my model I get what seems to be an obnoxiously high number of support vectors and a terrible "best performance" of 12% using tune. From eyeballing the data it should be very simple for an SVM to place a hyperplane that divides the classes. when I run model$coefs it shows me all the coefs have the same value as the cost. I must be doing something wrong. Can anyone tell me where my mistake is? Surely it is possible to have better performance than 12%.

Here is my data https://drive.google.com/file/d/17NzAy6V5uZ4lZC7sm0Ou3ooZ01-Tw0jX/view?usp=sharing. When I run


says best parameter for cost is 0.01 and best performance is 0.1273417.


gives me 1224 support vectors if I ask it to show me the coefs model$coefs they are all 0.01 or -0.01.

Here is what the data looks like in excel


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