for 1. you can definitely modify an SVM to be used for regression, as far as I know most standard SVM libraries have support for regression, and I have personally used them very successfully for this task. [0]
2. There are actually ways you can modify the output of an SVM to give a probabilistic interpretation[1]. But I'll agree with the not having a 'natural' probabilistic interpretation.
3. Is definitely correct, but I'm not sure NNs are that much better.
2. There are actually ways you can modify the output of an SVM to give a probabilistic interpretation[1]. But I'll agree with the not having a 'natural' probabilistic interpretation.
3. Is definitely correct, but I'm not sure NNs are that much better.
[0] http://www.svms.org/regression/
[1] http://www.cs.colorado.edu/~mozer/Teaching/syllabi/6622/pape...