struct feature_node{ int index; double value;};struct problem{ struct feature_node **x;};problem prob;/* `x' is an array of pointers, each of which points to a sparse representation (array of feature_node) of one training vector. For example, if we have the following training data: LABEL ATTR1 ATTR2 ATTR3 ATTR4 ATTR5 ----- ----- ----- ----- ----- ----- 1 0 0.1 0.2 0 0 2 0 0.1 0.3 -1.2 0 1 0.4 0 0 0 0 2 0 0.1 0 1.4 0.5 3 -0.1 -0.2 0.1 1.1 0.1 and bias = 1, then the components of problem are: l = 5 n = 6 y -> 1 2 1 2 3 x -> [ ] -> (2,0.1) (3,0.2) (6,1) (-1,?) [ ] -> (2,0.1) (3,0.3) (4,-1.2) (6,1) (-1,?) [ ] -> (1,0.4) (6,1) (-1,?) [ ] -> (2,0.1) (4,1.4) (5,0.5) (6,1) (-1,?) [ ] -> (1,-0.1) (2,-0.2) (3,0.1) (4,1.1) (5,0.1) (6,1) (-1,?)*/