Simple training and testing issue using libsvm C++ in Eclipse -

i trying execute simple xor output prediction using libsvm c++ in eclipse. code have written. output value should predicting a+1 have error cannot solve:

expected expression before ')' token.

this line error:

#define malloc(type,n) (type *)malloc((n)*sizeof(type))" 

what doing wrong?

#include <stdio.h> #include <stdlib.h> #include <string.h> #include <ctype.h> #include <errno.h> #include "libsvm.h" #include "main.h"  #define malloc(type,n) (type *)malloc((n)*sizeof(type)) // struct svm_node *x = (struct svm_node *) malloc((n+1)*sizeof(struct svm_node));  struct svm_parameter param;     // set parse_command_line struct svm_problem prob;        // set read_problem struct svm_model *model; struct svm_node *x_space; struct svm_node ** x; struct svm_node *testnode;  void makemodel2(void) // int main(int argc, char **argv) {     //char input_file_name[1024];     //char model_file_name[1024];     //const char *error_msg;      param.svm_type = c_svc;     param.kernel_type = rbf;     param.degree = 3;     param.gamma = 0.5;     param.coef0 = 0;     param.nu = 0.5;     param.cache_size = 100;     param.c = 1;     param.eps = 1e-3;     param.p = 0.1;     param.shrinking = 1;     param.probability = 0;     param.nr_weight = 0;     param.weight_label = null;     param.weight = null;      // --- problem definition ---     prob.l = 4;      //x values matrix of xor values     double matrix[prob.l][2];     matrix[0][0] = 1;     matrix[0][1] = 1;      matrix[1][0] = 1;     matrix[1][1] = 0;      matrix[2][0] = 0;     matrix[2][1] = 1;      matrix[3][0] = 0;     matrix[3][1] = 0;      //this part have trouble understanding     struct svm_node** x = (struct svm_node * *)malloc((prob.l)*sizeof(struct svm_node *));     // svm_node** x = malloc(svm_node*,prob.l);     // (x *)malloc((prob.l)*sizeof(prob.l))     // x = malloc(x,prob.l);      //trying assign matrix svm_node training examples     (int row = 0;row <prob.l; row++){         x_space = malloc(x_space,3);         // svm_node* x_space = malloc(svm_node,3);         // x_space = malloc(x_space,3);         // struct svm_node *x_space = (struct svm_node *) malloc((3)*sizeof(struct svm_node));         (int col = 0;col < 2;col++){             x_space[col].index = col;             x_space[col].value = matrix[row][col];         }         //each row of properties should terminated -1 according readme         x_space[2].index = -1;               x[row] = x_space;     }      prob.x = x;      //yvalues     prob.y = (double *)malloc((prob.l)*sizeof(double));     // prob.y = malloc(double,prob.l); // prob.y = malloc(prob.y,prob.l);     prob.y[0] = -1;     prob.y[1] = 1;     prob.y[2] = 1;     prob.y[3] = -1;      // --- train model---     model = svm_train(&prob,&param);     // svm_model *model = svm_train(&prob,&param);       // --- test model ---     struct svm_node *testnode = (struct svm_node *) malloc((3)*sizeof(struct svm_node));     // svm_node* testnode = malloc(svm_node,3);     // testnode = malloc(testnode,3);     // testnode = malloc(testnode,3);     testnode[0].index = 0;     testnode[0].value = 1;     testnode[1].index = 1;     testnode[1].value = 0;     testnode[2].index = -1;      //this works correctly:     retval[0] = svm_predict(model,testnode);     // double retval = svm_predict(model,testnode);     //printf("retval: %f\n",retval);      svm_destroy_param(&param);     free(prob.y);     free(prob.x);     free(x_space);      //return 0; }