The linear separability problem can be characterized as:

A a$)$ The fact that a single neuron, despite extensive training, can only create a hyperplane decision surface.

b$)$ A situation where different "classes" of data can be separated into their classes by straight lines.

c$)$ A situation where different "classes" of data cannot be separated into their classes by straight lines.

d$)$ Both $($a$)$ and $($b$)$ above.

e$)$ Both $($a$)$ and $($c$)$ above.

f$)$ None of the above.