LLM4Binary/decompile-bench-makefile huggingface dataset:
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/rbf.c
// Function: rbf_forward_propagation
void rbf_forward_propagation(Rbfnetworkptr network, Instanceptr inst, double* p, double* y)
{
	/*!Last Changed 19.08.2007*/
 double dist, s_h;
	int i, h;
	p[0] = 1.0;
	for (h = 1; h < network->hidden + 1; h++)
  {
   dist = distance_to_rbf_gaussian(inst, network->input, network->weights.m.values[h - 1]);
   s_h = network->weights.s.values[0][h - 1];
			p[h] = safeexp(-dist / (2 * s_h * s_h));
  }
	for (i = 0; i < network->output; i++)
	 {
		 y[i] = 0.0;
			for (h = 0; h < network->hidden + 1; h++)
				 y[i] += network->weights.w.values[i][h] * p[h];
	 }
	if (network->output > 1) /*For classification*/
  	softmax(y, network->output);
}

// Assembly:
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
movq %rcx, %rbx
movq %rdx, %r14
movq %rdi, %r15
movabsq $0x3ff0000000000000, %rax # imm = 0x3FF0000000000000
movq %rax, (%rdx)
movl (%rdi), %eax
testl %eax, %eax
jle 0x6ff03
movq %rsi, %r12
xorl %r13d, %r13d
movl 0x8(%r15), %esi
movq 0x18(%r15), %rax
movq (%rax,%r13,8), %rdx
movq %r12, %rdi
callq 0x6fe07
movq 0x28(%r15), %rax
movq (%rax), %rax
movsd (%rax,%r13,8), %xmm1
xorpd 0x362f4(%rip), %xmm0    # 0xa61d0
movapd %xmm1, %xmm2
addsd %xmm1, %xmm2
mulsd %xmm1, %xmm2
divsd %xmm2, %xmm0
callq 0x39bb5
movsd %xmm0, 0x8(%r14,%r13,8)
movslq (%r15), %rax
incq %r13
cmpq %rax, %r13
jl 0x6feb3
movslq 0x4(%r15), %rsi
testq %rsi, %rsi
jle 0x6ff56
leal 0x1(%rax), %ecx
xorl %edx, %edx
movq $0x0, (%rbx,%rdx,8)
testl %eax, %eax
js 0x6ff49
movq 0x38(%r15), %rdi
movq (%rdi,%rdx,8), %rdi
xorpd %xmm0, %xmm0
xorl %r8d, %r8d
movsd (%rdi,%r8,8), %xmm1
mulsd (%r14,%r8,8), %xmm1
addsd %xmm1, %xmm0
movsd %xmm0, (%rbx,%rdx,8)
incq %r8
cmpq %r8, %rcx
jne 0x6ff2c
incq %rdx
cmpq %rsi, %rdx
jne 0x6ff11
cmpl $0x1, %esi
jne 0x6ff60
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
retq
movq %rbx, %rdi
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
jmp 0x55aa4
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/rbf.c
// Function: real_actual_difference
double real_actual_difference(int output, Instanceptr inst, int classno, double* y)
{
	/*!Last Changed 19.08.2007*/
	double ri;
 if (output == 1)
			ri = give_regressionvalue(inst);
	else
			if (give_classno(inst) != classno)
				 ri = 0.0;
			else
					ri = 1.0;
	return ri - y[classno];
}

// Assembly:
pushq %rbp
pushq %rbx
pushq %rax
movq %rcx, %rbx
movl %edx, %ebp
cmpl $0x1, %edi
jne 0x6ff88
movq %rsi, %rdi
callq 0x2f35e
jmp 0x6ffa2
movq %rsi, %rdi
callq 0x2f33a
cmpl %ebp, %eax
je 0x6ff9a
xorpd %xmm0, %xmm0
jmp 0x6ffa2
movsd 0x3557e(%rip), %xmm0    # 0xa5520
movslq %ebp, %rax
subsd (%rbx,%rax,8), %xmm0
addq $0x8, %rsp
popq %rbx
popq %rbp
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/rbf.c
// Function: update_rbfweights
void update_rbfweights(Rbfnetworkptr network, Rbfweights delta, Rbfweights prevweights, Rbf_parameterptr params)
{
 /*!Last Changed 21.08.2007*/
 int i, h, j;
 for (i = 0; i < network->output; i++)
   for (h = 0; h < network->hidden + 1; h++)
     network->weights.w.values[i][h] = network->weights.w.values[i][h] + delta.w.values[i][h] + params->alpha * prevweights.w.values[i][h];
 for (h = 0; h < network->hidden; h++)
   for (j = 0; j < network->input; j++)
     network->weights.m.values[h][j] = network->weights.m.values[h][j] + delta.m.values[h][j] + params->alpha * prevweights.m.values[h][j];
 for (h = 0; h < network->hidden; h++)
   network->weights.s.values[0][h] = network->weights.s.values[0][h] + delta.s.values[0][h] + params->alpha * prevweights.s.values[0][h];
}

// Assembly:
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
leaq 0x60(%rsp), %rcx
leaq 0x30(%rsp), %rdx
movslq 0x4(%rdi), %r8
movl (%rdi), %eax
testq %r8, %r8
jle 0x702bf
movq 0x28(%rdx), %r9
movq 0x28(%rcx), %r10
leal 0x1(%rax), %r11d
xorl %ebx, %ebx
testl %eax, %eax
js 0x702b7
movq 0x38(%rdi), %r14
movq (%r14,%rbx,8), %r14
movq (%r9,%rbx,8), %r15
movq (%r10,%rbx,8), %r12
xorl %r13d, %r13d
movsd (%r14,%r13,8), %xmm0
addsd (%r15,%r13,8), %xmm0
movsd 0x38(%rsi), %xmm1
mulsd (%r12,%r13,8), %xmm1
addsd %xmm0, %xmm1
movsd %xmm1, (%r14,%r13,8)
incq %r13
cmpq %r13, %r11
jne 0x7028e
incq %rbx
cmpq %r8, %rbx
jne 0x70277
testl %eax, %eax
jle 0x70364
movl 0x8(%rdi), %r8d
movq 0x8(%rdx), %r9
movq 0x8(%rcx), %r10
xorl %r11d, %r11d
testl %r8d, %r8d
jle 0x70317
movq 0x18(%rdi), %rbx
movq (%rbx,%r11,8), %rbx
movq (%r9,%r11,8), %r14
movq (%r10,%r11,8), %r15
xorl %r12d, %r12d
movsd (%rbx,%r12,8), %xmm0
addsd (%r14,%r12,8), %xmm0
movsd 0x38(%rsi), %xmm1
mulsd (%r15,%r12,8), %xmm1
addsd %xmm0, %xmm1
movsd %xmm1, (%rbx,%r12,8)
incq %r12
cmpq %r12, %r8
jne 0x702ee
incq %r11
cmpq %rax, %r11
jne 0x702d6
testl %eax, %eax
jle 0x70364
movq 0x28(%rdi), %rdi
movq (%rdi), %rdi
movq 0x18(%rdx), %rdx
movq (%rdx), %rdx
movq 0x18(%rcx), %rcx
movq (%rcx), %rcx
xorl %r8d, %r8d
movsd (%rdi,%r8,8), %xmm0
addsd (%rdx,%r8,8), %xmm0
movsd 0x38(%rsi), %xmm1
mulsd (%rcx,%r8,8), %xmm1
addsd %xmm0, %xmm1
movsd %xmm1, (%rdi,%r8,8)
incq %r8
cmpq %r8, %rax
jne 0x7033b
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/rbf.c
// Function: test_rbfnetwork_cls
int test_rbfnetwork_cls(Rbfnetworkptr network, Instanceptr data)
{
	/*!Last Changed 19.08.2007*/
	double *p, *y;
	Instanceptr inst;
	int correct = 0, classno;
	p = safemalloc((network->hidden + 1) * sizeof(double), "test_rbfnetwork_cls", 3);
	y = safemalloc(network->output * sizeof(double), "test_rbfnetwork_cls", 4);
	inst = data;
	while (inst)
	 {
		 rbf_forward_propagation(network, inst, p, y);
			classno = findMaxOutput(y, network->output);
			if (classno == give_classno(inst))
				 correct++;
		 inst = inst->next;
	 }
	safe_free(p);
	safe_free(y);
	return correct;
}

// Assembly:
pushq %rbp
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
pushq %rax
movq %rsi, %rbx
movq %rdi, %r14
movslq (%rdi), %rax
leaq 0x8(,%rax,8), %rdi
leaq 0x3f3a4(%rip), %r12     # 0xaf735
movq %r12, %rsi
movl $0x3, %edx
callq 0x3a0e1
movq %rax, %r15
movslq 0x4(%r14), %rdi
shlq $0x3, %rdi
movq %r12, %rsi
movl $0x4, %edx
callq 0x3a0e1
movq %rax, %r12
xorl %ebp, %ebp
testq %rbx, %rbx
je 0x703f8
movq %r14, %rdi
movq %rbx, %rsi
movq %r15, %rdx
movq %r12, %rcx
callq 0x6fe88
movl 0x4(%r14), %esi
movq %r12, %rdi
callq 0x38362
movl %eax, %r13d
movq %rbx, %rdi
callq 0x2f33a
xorl %ecx, %ecx
cmpl %eax, %r13d
sete %cl
addl %ecx, %ebp
movq 0x10(%rbx), %rbx
jmp 0x703bb
movq %r15, %rdi
callq 0x3a180
movq %r12, %rdi
callq 0x3a180
movl %ebp, %eax
addq $0x8, %rsp
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
popq %rbp
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/rbf.c
// Function: test_rbfnetwork_reg
double test_rbfnetwork_reg(Rbfnetworkptr network, Instanceptr data)
{
	/*!Last Changed 19.08.2007*/
	double *p, *y, squaredError = 0.0;
	Instanceptr inst;
	p = safemalloc((network->hidden + 1) * sizeof(double), "test_rbfnetwork_reg", 3);
	y = safemalloc(sizeof(double), "test_rbfnetwork_reg", 4);
	inst = data;
	while (inst)
	 {
		 rbf_forward_propagation(network, inst, p, y);
			squaredError += (y[0] - give_regressionvalue(inst)) * (y[0] - give_regressionvalue(inst));
		 inst = inst->next;
	 }
	safe_free(p);
	safe_free(y);
	return squaredError;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r12
pushq %rbx
subq $0x18, %rsp
movq %rsi, %rbx
movq %rdi, %r14
movslq (%rdi), %rax
leaq 0x8(,%rax,8), %rdi
leaq 0x3ef99(%rip), %r12     # 0xaf75e
movq %r12, %rsi
movl $0x3, %edx
callq 0x3a0e1
movq %rax, %r15
movl $0x8, %edi
movq %r12, %rsi
movl $0x4, %edx
callq 0x3a0e1
movq %rax, %r12
xorpd %xmm0, %xmm0
testq %rbx, %rbx
je 0x7086a
movsd %xmm0, (%rsp)
movq %r14, %rdi
movq %rbx, %rsi
movq %r15, %rdx
movq %r12, %rcx
callq 0x6fe88
movsd (%r12), %xmm0
movsd %xmm0, 0x8(%rsp)
movq %rbx, %rdi
callq 0x2f35e
movsd 0x8(%rsp), %xmm1
subsd %xmm0, %xmm1
movsd %xmm1, 0x8(%rsp)
movsd (%r12), %xmm0
movsd %xmm0, 0x10(%rsp)
movq %rbx, %rdi
callq 0x2f35e
movsd 0x10(%rsp), %xmm1
subsd %xmm0, %xmm1
mulsd 0x8(%rsp), %xmm1
movsd (%rsp), %xmm0
addsd %xmm1, %xmm0
movsd %xmm0, (%rsp)
movq 0x10(%rbx), %rbx
testq %rbx, %rbx
jne 0x707f8
jmp 0x7086f
movsd %xmm0, (%rsp)
movq %r15, %rdi
callq 0x3a180
movq %r12, %rdi
callq 0x3a180
movsd (%rsp), %xmm0
addq $0x18, %rsp
popq %rbx
popq %r12
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: print_regression_results
void print_regression_results(Instanceptr testdata, Regressionresultptr result, double runtime, int printbinary, int displayruntime)
{
 /*!Last Changed 25.05.2006 added regression value*/
	/*!Last Changed 13.12.2004 added printbinary*/
 /*!Last Changed 10.03.2004*/
	char pst[READLINELENGTH], pst2[READLINELENGTH];
	int i;
 double regvalue;
 Instanceptr tmp;
	if (printbinary)
	 {
   set_precision(pst, NULL, "\n");
   set_precision(pst2, NULL, " ");
   tmp = testdata;
		 for (i = 0; i < result->datasize; i++)
    {
     regvalue = give_regressionvalue(tmp);
     fprintf(output, "%d ", tmp->index);
     fprintf(output, pst2, regvalue);
     fprintf(output, pst, result->absoluteerrors[i]);
     tmp = tmp->next;
    }
	 }
	else
  	if (displayruntime)
			 {
				 set_precision(pst, NULL, " %.3lf\n");
	  		fprintf(output, pst, result->regressionperformance / result->datasize, runtime); 		 
			 }
	  else
			 {
				 set_precision(pst, NULL, "\n");
		  	fprintf(output, pst, result->regressionperformance / result->datasize); 		 
			 }
}

// Assembly:
pushq %rbp
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
subq $0xf4258, %rsp          # imm = 0xF4258
movq %rsi, %rbx
testl %edx, %edx
je 0x72299
movq %rdi, %r14
leaq 0x36fa9(%rip), %rdx     # 0xa919b
leaq 0x10(%rsp), %rdi
xorl %esi, %esi
callq 0x3a535
leaq 0x364e0(%rip), %rdx     # 0xa86e5
leaq 0x7a130(%rsp), %rdi
xorl %esi, %esi
callq 0x3a535
cmpl $0x0, 0x10(%rbx)
jle 0x7231b
leaq 0x33fe83(%rip), %rbp    # 0x3b20a8
leaq 0x7a130(%rsp), %r12
leaq 0x10(%rsp), %r13
xorl %r15d, %r15d
movq %r14, %rdi
callq 0x2f35e
movsd %xmm0, 0x8(%rsp)
movq (%rbp), %rdi
movl 0x18(%r14), %edx
leaq 0x3db33(%rip), %rsi     # 0xafd85
xorl %eax, %eax
callq 0x42e0
movq (%rbp), %rdi
movq %r12, %rsi
movsd 0x8(%rsp), %xmm0
movb $0x1, %al
callq 0x42e0
movq (%rbp), %rdi
movq (%rbx), %rax
movsd (%rax,%r15,8), %xmm0
movq %r13, %rsi
movb $0x1, %al
callq 0x42e0
movq 0x10(%r14), %r14
incq %r15
movslq 0x10(%rbx), %rax
cmpq %rax, %r15
jl 0x72235
jmp 0x7231b
testl %ecx, %ecx
je 0x722e3
leaq 0x33b8f(%rip), %rdx     # 0xa5e33
leaq 0x10(%rsp), %r14
movq %r14, %rdi
xorl %esi, %esi
movsd %xmm0, 0x8(%rsp)
callq 0x3a535
leaq 0x33fde8(%rip), %rax    # 0x3b20a8
movq (%rax), %rdi
movsd 0x8(%rbx), %xmm0
cvtsi2sdl 0x10(%rbx), %xmm1
divsd %xmm1, %xmm0
movq %r14, %rsi
movsd 0x8(%rsp), %xmm1
movb $0x2, %al
callq 0x42e0
jmp 0x7231b
leaq 0x36eb1(%rip), %rdx     # 0xa919b
leaq 0x10(%rsp), %r14
movq %r14, %rdi
xorl %esi, %esi
callq 0x3a535
leaq 0x33fda8(%rip), %rax    # 0x3b20a8
movq (%rax), %rdi
movsd 0x8(%rbx), %xmm0
cvtsi2sdl 0x10(%rbx), %xmm1
divsd %xmm1, %xmm0
movq %r14, %rsi
movb $0x1, %al
callq 0x42e0
addq $0xf4258, %rsp          # imm = 0xF4258
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
popq %rbp
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: performance_initialize_regression
Regressionresultptr performance_initialize_regression(int datasize)
{
	/*!Last Changed 13.12.2004*/
 Regressionresultptr result;
 result = safemalloc(sizeof(Regressionresult), "performance_initialize_regression", 2);
	result->regressionperformance = 0;
 result->absoluteerrors = safemalloc(datasize * sizeof(double), "performance_initialize_regression", 4);
 result->datasize = datasize;
 result->epsilonloss = 0.0;
 return result;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r12
pushq %rbx
pushq %rax
movl %edi, %ebx
leaq 0x3d733(%rip), %r14     # 0xafa71
movl $0x20, %edi
movq %r14, %rsi
movl $0x2, %edx
callq 0x3a0e1
movq %rax, %r15
xorl %r12d, %r12d
movq %r12, 0x8(%rax)
movslq %ebx, %rbx
leaq (,%rbx,8), %rdi
movq %r14, %rsi
movl $0x4, %edx
callq 0x3a0e1
movq %rax, (%r15)
movl %ebx, 0x10(%r15)
movq %r12, 0x18(%r15)
movq %r15, %rax
addq $0x8, %rsp
popq %rbx
popq %r12
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: train_onefeature
void* train_onefeature(Instanceptr* trdata, Instanceptr *cvdata, void* parameters)
{
	/*!Last Changed 11.08.2005 added model for onefeature algorithm*/
	/*!Last Changed 10.12.2004*/
	char dummy;
 Model_onefeatureptr m;
	Instanceptr leftgroup = NULL, rightgroup = NULL;
	m = safemalloc(sizeof(Model_onefeature), "train_onefeature", 4);
	m->bestfeature = best_regression_feature(*trdata, &(m->bestsplit), &dummy);
	divide_instancelist_according_to_split(trdata, &leftgroup, &rightgroup, m->bestfeature, m->bestsplit);
	m->leftmean = find_mean_of_regression_value(leftgroup);
	m->rightmean = find_mean_of_regression_value(rightgroup);
	deallocate(leftgroup);
	deallocate(rightgroup);
	return m;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r12
pushq %rbx
subq $0x18, %rsp
movq %rdi, %r12
xorl %eax, %eax
leaq 0x10(%rsp), %r14
movq %rax, (%r14)
leaq 0x8(%rsp), %rbx
movq %rax, (%rbx)
leaq 0x3d6cb(%rip), %rsi     # 0xafa93
movl $0x20, %edi
movl $0x4, %edx
callq 0x3a0e1
movq %rax, %r15
movq (%r12), %rdi
leaq 0x8(%rax), %rsi
leaq 0x7(%rsp), %rdx
callq 0x76c85
movl %eax, (%r15)
movsd 0x8(%r15), %xmm0
movq %r12, %rdi
movq %r14, %rsi
movq %rbx, %rdx
movl %eax, %ecx
callq 0x30ade
movq (%r14), %rdi
callq 0x2ffe1
movsd %xmm0, 0x10(%r15)
movq (%rbx), %rdi
callq 0x2ffe1
movsd %xmm0, 0x18(%r15)
movq (%r14), %rdi
callq 0x2ff55
movq (%rbx), %rdi
callq 0x2ff55
movq %r15, %rax
addq $0x18, %rsp
popq %rbx
popq %r12
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: test_knnreg
Prediction test_knnreg(Instanceptr data, void* model, void* parameters, double* posterior)
{
	/*!Last Changed 19.04.2004*/
	/*!Last Changed 10.03.2004*/
	int i;
	Prediction predicted;
	Instanceptr *nearestneighbors, trdata;
	Knn_parameterptr p;
 p = (Knn_parameterptr) parameters;
	trdata = (Instanceptr) model;
 if (current_dataset->storetype == STORE_KERNEL)
   nearestneighbors = find_all_neighbors(trdata, data, &(p->nearcount));
 else
	  nearestneighbors = find_nearest_neighbors(trdata, data, p->nearcount);
	predicted.regvalue = 0;
 for (i = 0; i < p->nearcount; i++)
			predicted.regvalue += give_regressionvalue(nearestneighbors[i]);
	predicted.regvalue /= p->nearcount;
	safe_free(nearestneighbors);
 return predicted;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r12
pushq %rbx
pushq %rax
movq %rcx, %r14
movq %rdx, %rax
movq %rdi, %rbx
leaq 0x633f0(%rip), %rcx     # 0xd5870
movq (%rcx), %rcx
cmpl $0x3, 0x140713c(%rcx)
jne 0x72499
movq %rax, %rdi
movq %r14, %rdx
callq 0x313ff
jmp 0x724a4
movl (%r14), %edx
movq %rax, %rdi
callq 0x3151c
movq %rax, %r15
movl (%r14), %eax
xorpd %xmm1, %xmm1
testl %eax, %eax
jle 0x724d7
xorl %r12d, %r12d
movsd %xmm1, (%rsp)
movq (%r15,%r12,8), %rdi
callq 0x2f35e
movsd (%rsp), %xmm1
addsd %xmm0, %xmm1
incq %r12
movslq (%r14), %rax
cmpq %rax, %r12
jl 0x724b5
xorps %xmm0, %xmm0
cvtsi2sd %eax, %xmm0
divsd %xmm0, %xmm1
movsd %xmm1, (%rbx)
movq %r15, %rdi
callq 0x3a180
movq %rbx, %rax
addq $0x8, %rsp
popq %rbx
popq %r12
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: train_regstump
void* train_regstump(Instanceptr* trdata, Instanceptr *cvdata, void* parameters)
{
	Regressionnodeptr regtreenode;
	Regtree_parameterptr p;
	p = (Regtree_parameterptr) parameters;
 regtreenode = createnewregnode(NULL, 1, p->leaftype);
 regtreenode->cvinstances = *trdata;
 regtreenode->instances = *trdata;
	regtreenode->featureno = best_hybrid_regression_tree_split(regtreenode, p);
 make_regression_children(regtreenode, p->leaftype);
 setup_regressionnode_properties(regtreenode->left, p->leaftype);
 setup_regressionnode_properties(regtreenode->right, p->leaftype);
 make_leaf_regression_node(regtreenode->left, p->leaftype);
 make_leaf_regression_node(regtreenode->right, p->leaftype);
	*trdata = NULL;
	return regtreenode;
}

// Assembly:
pushq %r15
pushq %r14
pushq %rbx
movq %rdx, %r14
movq %rdi, %rbx
movl (%rdx), %edx
xorl %edi, %edi
movl $0x1, %esi
callq 0x7710e
movq %rax, %r15
movq (%rbx), %rax
movq %rax, 0x28(%r15)
movq %rax, 0x20(%r15)
movq %r15, %rdi
movq %r14, %rsi
callq 0x7854c
movl %eax, 0x68(%r15)
movl (%r14), %esi
movq %r15, %rdi
callq 0x77381
movq (%r15), %rdi
movl (%r14), %esi
callq 0x7777a
movq 0x8(%r15), %rdi
movl (%r14), %esi
callq 0x7777a
movq (%r15), %rdi
movl (%r14), %esi
callq 0x766ca
movq 0x8(%r15), %rdi
movl (%r14), %esi
callq 0x766ca
movq $0x0, (%rbx)
movq %r15, %rax
popq %rbx
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: test_regressiontree
Prediction test_regressiontree(Instanceptr data, void* model, void* parameters, double* posterior)
{
	/*!Last Changed 06.03.2005*/
	/*!Last Changed 09.12.2004*/
	Regressionnodeptr regtreenode;
 Prediction predicted;
	regtreenode = (Regressionnodeptr) model;
 while (regtreenode->featureno != -1)
   regtreenode = next_regression_node(regtreenode, data); 
 if (regtreenode->leaftype == CONSTANTLEAF)
   predicted.regvalue = regtreenode->regressionvalue;
 else
   predicted.regvalue = linear_fit_value(regtreenode->w, data);
 return predicted;
}

// Assembly:
pushq %r14
pushq %rbx
pushq %rax
movq %rdx, %rax
movq %rsi, %r14
movq %rdi, %rbx
cmpl $-0x1, 0x68(%rdx)
je 0x725ae
movq %rax, %rdi
movq %r14, %rsi
callq 0x771fc
cmpl $-0x1, 0x68(%rax)
jne 0x7259d
cmpl $0x0, 0x6c(%rax)
je 0x725c6
movq 0x30(%rax), %rdi
movq 0x38(%rax), %rsi
movq %r14, %rdx
callq 0x76f0b
jmp 0x725cb
movsd 0x70(%rax), %xmm0
movsd %xmm0, (%rbx)
movq %rbx, %rax
addq $0x8, %rsp
popq %rbx
popq %r14
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: train_softregstump
void* train_softregstump(Instanceptr* trdata, Instanceptr *cvdata, void* parameters)
{
	Regressionnodeptr regtreenode;
	Softregtree_parameterptr p;
	p = (Softregtree_parameterptr) parameters;
 regtreenode = createnewregnode(NULL, 1, p->leaftype);
 regtreenode->weight = 1.0;
 regtreenode->instances = *trdata;
 if (p->leaftype == CONSTANTLEAF)
   regtreenode->regressionvalue = produce_random_value(-0.01, +0.01);
 else
   regtreenode->w = random_matrix(current_dataset->multifeaturecount, 1, -0.01, +0.01);
 regtreenode->cvinstances = NULL;
 find_best_soft_regtree_split(regtreenode, regtreenode, *trdata, p);
 make_leaf_regression_node(regtreenode->left, p->leaftype);
 make_leaf_regression_node(regtreenode->right, p->leaftype);
 if (regtreenode->featureno != LEAF_NODE)
   deallocate(regtreenode->instances);
	*trdata = NULL;
	return regtreenode;
}

// Assembly:
pushq %r15
pushq %r14
pushq %rbx
movq %rdx, %r15
movq %rdi, %rbx
movl (%rdx), %edx
xorl %edi, %edi
movl $0x1, %esi
callq 0x7710e
movq %rax, %r14
movabsq $0x3ff0000000000000, %rax # imm = 0x3FF0000000000000
movq %rax, 0x48(%r14)
movq (%rbx), %rax
movq %rax, 0x20(%r14)
cmpl $0x0, (%r15)
je 0x72645
leaq 0x63258(%rip), %rax     # 0xd5870
movq (%rax), %rax
movl 0x1c0(%rax), %edi
movsd 0x3378f(%rip), %xmm0    # 0xa5db8
movsd 0x3378f(%rip), %xmm1    # 0xa5dc0
movl $0x1, %esi
callq 0x3ef18
movq %rax, 0x30(%r14)
movq %rdx, 0x38(%r14)
jmp 0x72660
movsd 0x3376b(%rip), %xmm0    # 0xa5db8
movsd 0x3376b(%rip), %xmm1    # 0xa5dc0
callq 0x3af6a
movsd %xmm0, 0x70(%r14)
movq $0x0, 0x28(%r14)
movq (%rbx), %rdx
movq %r14, %rdi
movq %r14, %rsi
movq %r15, %rcx
callq 0x8af0e
movq (%r14), %rdi
movl (%r15), %esi
callq 0x766ca
movq 0x8(%r14), %rdi
movl (%r15), %esi
callq 0x766ca
cmpl $-0x1, 0x68(%r14)
je 0x726a0
movq 0x20(%r14), %rdi
callq 0x2ff55
movq $0x0, (%rbx)
movq %r14, %rax
popq %rbx
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: train_regressiontree
void* train_regressiontree(Instanceptr* trdata, Instanceptr *cvdata, void* parameters)
{
 /*!Last Changed 25.05.2006 added in_list ...*/
	/*!Last Changed 06.03.2005*/
	/*!Last Changed 09.12.2004*/
	Regressionnodeptr regtreenode;
	Regtree_parameterptr p;
	p = (Regtree_parameterptr) parameters;
 regtreenode = createnewregnode(NULL, 1, p->leaftype);
 regtreenode->cvinstances = *cvdata;
 regtreenode->instances = *trdata;
	create_regtree(regtreenode, p);
 if (in_list(p->modelselectionmethod, 3, MODEL_SELECTION_CV, MODEL_SELECTION_AIC, MODEL_SELECTION_BIC) || p->prunetype == VALIDATIONPRUNING)
  	prune_regression_tree(regtreenode, p);
	*trdata = NULL;
	return regtreenode;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r12
pushq %rbx
pushq %rax
movq %rdx, %r14
movq %rsi, %r12
movq %rdi, %rbx
movl (%rdx), %edx
xorl %edi, %edi
movl $0x1, %esi
callq 0x7710e
movq %rax, %r15
movq (%r12), %rax
movq %rax, 0x28(%r15)
movq (%rbx), %rax
movq %rax, 0x20(%r15)
movq %r15, %rdi
movq %r14, %rsi
callq 0x785ed
movl 0x8(%r14), %edi
movl $0x3, %esi
xorl %edx, %edx
movl $0x1, %ecx
movl $0x2, %r8d
xorl %eax, %eax
callq 0x3aa8c
testl %eax, %eax
jne 0x7273e
cmpl $0x1, 0x4(%r14)
jne 0x72749
movq %r15, %rdi
movq %r14, %rsi
callq 0x775d9
movq $0x0, (%rbx)
movq %r15, %rax
addq $0x8, %rsp
popq %rbx
popq %r12
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: train_softregressiontree
void* train_softregressiontree(Instanceptr* trdata, Instanceptr *cvdata, void* parameters)
{
	Regressionnodeptr regtreenode;
	Softregtree_parameterptr p;
	p = (Softregtree_parameterptr) parameters;
 regtreenode = createnewregnode(NULL, 1, p->leaftype);
 regtreenode->weight = 1.0;
 regtreenode->instances = *trdata;
 if (p->leaftype == CONSTANTLEAF)
   regtreenode->regressionvalue = produce_random_value(-0.01, +0.01);
 else
   regtreenode->w = random_matrix(current_dataset->multifeaturecount, 1, -0.01, +0.01);
 create_softregtree(regtreenode, regtreenode, *cvdata, p);
 if (regtreenode->featureno != LEAF_NODE)
   deallocate(regtreenode->instances);
 deallocate(*cvdata);
	*trdata = NULL;
	return regtreenode;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r12
pushq %rbx
pushq %rax
movq %rdx, %r12
movq %rsi, %r14
movq %rdi, %rbx
movl (%rdx), %edx
xorl %edi, %edi
movl $0x1, %esi
callq 0x7710e
movq %rax, %r15
movabsq $0x3ff0000000000000, %rax # imm = 0x3FF0000000000000
movq %rax, 0x48(%r15)
movq (%rbx), %rax
movq %rax, 0x20(%r15)
cmpl $0x0, (%r12)
je 0x727d1
leaq 0x630cc(%rip), %rax     # 0xd5870
movq (%rax), %rax
movl 0x1c0(%rax), %edi
movsd 0x33603(%rip), %xmm0    # 0xa5db8
movsd 0x33603(%rip), %xmm1    # 0xa5dc0
movl $0x1, %esi
callq 0x3ef18
movq %rax, 0x30(%r15)
movq %rdx, 0x38(%r15)
jmp 0x727ec
movsd 0x335df(%rip), %xmm0    # 0xa5db8
movsd 0x335df(%rip), %xmm1    # 0xa5dc0
callq 0x3af6a
movsd %xmm0, 0x70(%r15)
movq (%r14), %rdx
movq %r15, %rdi
movq %r15, %rsi
movq %r12, %rcx
callq 0x8b3a7
cmpl $-0x1, 0x68(%r15)
je 0x7280d
movq 0x20(%r15), %rdi
callq 0x2ff55
movq (%r14), %rdi
callq 0x2ff55
movq $0x0, (%rbx)
movq %r15, %rax
addq $0x8, %rsp
popq %rbx
popq %r12
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: train_svmregtree
void* train_svmregtree(Instanceptr* trdata, Instanceptr *cvdata, void* parameters)
{
 /*!Last Changed 01.11.2009*/
 Regressionnodeptr regtreenode;
 Regtree_parameterptr p;
 p = (Regtree_parameterptr) parameters;
 regtreenode = createnewregnode(NULL, 1, p->leaftype);
 regtreenode->cvinstances = *cvdata;
 regtreenode->instances = *trdata;
 create_svmregtree(regtreenode, p);
 if (in_list(p->modelselectionmethod, 3, MODEL_SELECTION_CV, MODEL_SELECTION_AIC, MODEL_SELECTION_BIC) || p->prunetype == VALIDATIONPRUNING)
   prune_regression_tree(regtreenode, p);
 *trdata = NULL;
 return regtreenode;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r12
pushq %rbx
pushq %rax
movq %rdx, %r14
movq %rsi, %r12
movq %rdi, %rbx
movl (%rdx), %edx
xorl %edi, %edi
movl $0x1, %esi
callq 0x7710e
movq %rax, %r15
movq (%r12), %rax
movq %rax, 0x28(%r15)
movq (%rbx), %rax
movq %rax, 0x20(%r15)
movq %r15, %rdi
movq %r14, %rsi
callq 0x94bb4
movl 0x8(%r14), %edi
movl $0x3, %esi
xorl %edx, %edx
movl $0x1, %ecx
movl $0x2, %r8d
xorl %eax, %eax
callq 0x3aa8c
testl %eax, %eax
jne 0x7288f
cmpl $0x1, 0x4(%r14)
jne 0x7289a
movq %r15, %rdi
movq %r14, %rsi
callq 0x775d9
movq $0x0, (%rbx)
movq %r15, %rax
addq $0x8, %rsp
popq %rbx
popq %r12
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: test_mlpgenericreg
Prediction test_mlpgenericreg(Instanceptr data, void* model, void* parameters, double* posterior)
{
	/*!Last Changed 08.12.2004 added matrix_free(cv)*/
 Mlpnetwork neuralnetwork;
	matrix test, testY, output_error;
 Prediction predicted;
 neuralnetwork = *((Mlpnetworkptr) model);
 output_error = matrix_alloc(1, 1);
	test = instancelist_to_matrix(data, REGRESSION, -1, MULTIVARIATE_LINEAR);
 testMlpnInput_reg(test.values[0], &testY, neuralnetwork, &output_error);
 matrix_free(output_error);
 matrix_free(testY);
	matrix_free(test);
 return predicted;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
subq $0x150, %rsp            # imm = 0x150
movq %rdx, %rax
movq %rsi, %r15
movq %rdi, %rbx
leaq 0xb8(%rsp), %r14
movl $0x98, %edx
movq %r14, %rdi
movq %rax, %rsi
callq 0x4310
movl $0x1, %edi
movl $0x1, %esi
callq 0x3d79d
leaq 0x98(%rsp), %r12
movq %rax, (%r12)
movq %rdx, 0x8(%r12)
movq %r15, %rdi
movl $0x1, %esi
movl $0xffffffff, %edx       # imm = 0xFFFFFFFF
movl $0xfffffffe, %ecx       # imm = 0xFFFFFFFE
callq 0x3008b
movq %rax, %r15
movq %rdx, %r13
movq (%rdx), %rax
movl $0x13, %ecx
movq %rsp, %rdi
movq %r14, %rsi
rep  movsq (%rsi), %es:(%rdi)
leaq 0xa8(%rsp), %r14
movq %rax, %rdi
movq %r14, %rsi
movq %r12, %rdx
callq 0x465cb
movq (%r12), %rdi
movq 0x8(%r12), %rsi
callq 0x3ed51
movq (%r14), %rdi
movq 0x8(%r14), %rsi
callq 0x3ed51
movq %r15, %rdi
movq %r13, %rsi
callq 0x3ed51
movq %rbx, %rax
addq $0x150, %rsp            # imm = 0x150
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: train_dncreg
void* train_dncreg(Instanceptr* trdata, Instanceptr *cvdata, void* parameters)
{
 /*!Last Changed 16.04.2007*/
 Mlpparameters mlpparams;
 Mlpnetworkptr neuralnetwork;
 matrix train;
 neuralnetwork = safemalloc(sizeof(Mlpnetwork), "train_dncreg", 4);
 mlpparams = *((Mlpparametersptr) parameters);
 mlpparams.inputnum = data_size(*trdata);
 mlpparams.trnum = mlpparams.inputnum;
 train = instancelist_to_matrix(*trdata, REGRESSION, -1, MULTIVARIATE_LINEAR);
 *neuralnetwork = dnc_reg(train, &mlpparams);
 matrix_free(train);
 return neuralnetwork;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
subq $0x130, %rsp            # imm = 0x130
movq %rdx, %r15
movq %rdi, %r12
leaq 0x3cf9b(%rip), %rsi     # 0xafac4
movl $0x98, %edi
movl $0x4, %edx
callq 0x3a0e1
movq %rax, %rbx
leaq 0x8(%rsp), %r14
movl $0x90, %edx
movq %r14, %rdi
movq %r15, %rsi
callq 0x4310
movq (%r12), %rdi
callq 0x30309
movl %eax, 0x8(%r14)
movl %eax, 0x10(%r14)
movq (%r12), %rdi
movl $0x1, %esi
movl $0xffffffff, %edx       # imm = 0xFFFFFFFF
movl $0xfffffffe, %ecx       # imm = 0xFFFFFFFE
callq 0x3008b
movq %rax, %r15
movq %rdx, %r12
leaq 0x98(%rsp), %r13
movq %r13, %rdi
movq %rax, %rsi
movq %r14, %rcx
callq 0x46f78
movl $0x98, %edx
movq %rbx, %rdi
movq %r13, %rsi
callq 0x4310
movq %r15, %rdi
movq %r12, %rsi
callq 0x3ed51
movq %rbx, %rax
addq $0x130, %rsp            # imm = 0x130
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: test_gprocessreg
Prediction test_gprocessreg(Instanceptr data, void* model, void* parameters, double* posterior)
{
 /*!Last Changed 15.01.2009*/
 int i;
 Prediction predicted;
 Gprocess_parameterptr gp;
 Model_gprocessregressionptr m;
 Instanceptr tmp;
 Svm_parameter param;
 Svm_nodeptr x, y;
 predicted.regvalue = 0.0;
 gp = (Gprocess_parameterptr) parameters;
 param.kernel_type = gp->kernel_type;
 param.coef0 = gp->coef0;
 param.gamma = gp->gamma;
 param.degree = gp->degree;
 m = (Model_gprocessregressionptr) model;
 y = instance_to_svmnode(data);
 tmp = m->data;
 for (i = 0; i < m->size; i++)
  {
   x = instance_to_svmnode(tmp);
   predicted.regvalue += k_function(x, y, param) * m->weights[i];
   safe_free(x);
   tmp = tmp->next;
  }
 safe_free(y);
 return predicted;
}

// Assembly:
pushq %rbp
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
subq $0xc8, %rsp
movq %rdx, %r14
movq %rdi, 0x68(%rsp)
movl 0x8(%rcx), %eax
movl %eax, 0x74(%rsp)
movsd 0x10(%rcx), %xmm0
movsd %xmm0, 0x88(%rsp)
movsd 0x20(%rcx), %xmm0
movsd %xmm0, 0x80(%rsp)
movl 0x18(%rcx), %eax
movl %eax, 0x78(%rsp)
movq %rsi, %rdi
callq 0x2ec9f
movq %rax, %r15
cmpl $0x0, (%r14)
jle 0x72f15
leaq 0x8(%r14), %r12
xorpd %xmm0, %xmm0
movsd %xmm0, 0x60(%rsp)
xorl %ebx, %ebx
leaq 0x70(%rsp), %r13
movq (%r12), %r12
movq %r12, %rdi
callq 0x2ec9f
movq %rax, %rbp
movl $0xb, %ecx
movq %rsp, %rdi
movq %r13, %rsi
rep  movsq (%rsi), %es:(%rdi)
movq %rax, %rdi
movq %r15, %rsi
callq 0x93d00
movq 0x10(%r14), %rax
mulsd (%rax,%rbx,8), %xmm0
movsd 0x60(%rsp), %xmm1
addsd %xmm0, %xmm1
movsd %xmm1, 0x60(%rsp)
movq %rbp, %rdi
callq 0x3a180
addq $0x10, %r12
incq %rbx
movslq (%r14), %rax
cmpq %rax, %rbx
jl 0x72ebb
jmp 0x72f1f
xorpd %xmm0, %xmm0
movsd %xmm0, 0x60(%rsp)
movq 0x68(%rsp), %rbx
movsd 0x60(%rsp), %xmm0
movsd %xmm0, (%rbx)
movq %r15, %rdi
callq 0x3a180
movq %rbx, %rax
addq $0xc8, %rsp
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
popq %rbp
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: test_linearregression
Prediction test_linearregression(Instanceptr data, void* model, void* parameters, double* posterior)
{
	/*!Last Changed 10.12.2004*/
	Model_linearregressionptr m;
	int i;
 Prediction predicted;
 predicted.regvalue = 0.0;
	m = (Model_linearregressionptr) model;
	for (i = 0; i < current_dataset->multifeaturecount - 1; i++)
		 predicted.regvalue += real_feature(data, i) * m->w.values[0][i];
	predicted.regvalue += m->b;
 return predicted;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
subq $0x10, %rsp
movq %rdx, %rbx
movq %rdi, %r14
leaq 0x6269f(%rip), %r13     # 0xd5870
movq (%r13), %rax
xorpd %xmm0, %xmm0
cmpl $0x2, 0x1c0(%rax)
jl 0x73232
movq %rsi, %r15
xorl %r12d, %r12d
movsd %xmm0, 0x8(%rsp)
movq %r15, %rdi
movl %r12d, %esi
callq 0x2ed6a
movq 0x10(%rbx), %rax
movq (%rax), %rax
mulsd (%rax,%r12,8), %xmm0
movsd 0x8(%rsp), %xmm1
addsd %xmm0, %xmm1
movsd %xmm1, 0x8(%rsp)
movsd 0x8(%rsp), %xmm0
incq %r12
movq (%r13), %rax
movslq 0x1c0(%rax), %rax
decq %rax
cmpq %rax, %r12
jl 0x731e8
addsd (%rbx), %xmm0
movsd %xmm0, (%r14)
movq %r14, %rax
addq $0x10, %rsp
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: test_quantizereg
Prediction test_quantizereg(Instanceptr data, void* model, void* parameters, double* posterior)
{
	/*!Last Changed 21.12.2004*/
	Model_quantizeregptr m;
	int x, y;
	double xvalue, yvalue;
 Prediction predicted;
	m = (Model_quantizeregptr) model;
	if (current_dataset->featurecount > 2)
		{
   dimension_reduce_with_pca(data, 2, m->eigenvectors);
			xvalue = real_feature(data, 0);
			yvalue = real_feature(data, 1);
			x = (int) ((xvalue - m->minx) / m->binx);
   check_and_put_in_between(&x, 0, m->partitioncount - 1);
			y = (int) ((yvalue - m->miny) / m->biny);
   check_and_put_in_between(&y, 0, m->partitioncount - 1);
   predicted.regvalue = m->meanstwo[x][y];
		}
	else
		{
			xvalue = real_feature(data, 0);
   x = (int) ((xvalue - m->minx) / m->binx);
   check_and_put_in_between(&x, 0, m->partitioncount - 1);
   predicted.regvalue = m->meansone[x];
  }
 return predicted;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r12
pushq %rbx
subq $0x28, %rsp
movq %rdx, %r14
movq %rsi, %r15
movq %rdi, %rbx
leaq 0x61c52(%rip), %rax     # 0xd5870
movq (%rax), %rax
cmpl $0x3, 0x1bc(%rax)
jl 0x73cd0
movq 0x30(%r14), %rdx
movq 0x38(%r14), %rcx
movq %r15, %rdi
movl $0x2, %esi
callq 0x10970
movq %r15, %rdi
xorl %esi, %esi
callq 0x2ed6a
movsd %xmm0, 0x10(%rsp)
movq %r15, %rdi
movl $0x1, %esi
callq 0x2ed6a
movsd %xmm0, 0x18(%rsp)
movsd 0x10(%rsp), %xmm0
subsd (%r14), %xmm0
divsd 0x8(%r14), %xmm0
cvttsd2si %xmm0, %eax
leaq 0xc(%rsp), %r12
movl %eax, (%r12)
movl 0x40(%r14), %edx
decl %edx
movq %r12, %rdi
xorl %esi, %esi
callq 0x3a8de
movsd 0x18(%rsp), %xmm0
subsd 0x10(%r14), %xmm0
divsd 0x18(%r14), %xmm0
cvttsd2si %xmm0, %eax
leaq 0x24(%rsp), %r15
movl %eax, (%r15)
movl 0x40(%r14), %edx
decl %edx
movq %r15, %rdi
xorl %esi, %esi
callq 0x3a8de
movslq (%r12), %rax
shlq $0x3, %rax
addq 0x28(%r14), %rax
jmp 0x73d08
movq %r15, %rdi
xorl %esi, %esi
callq 0x2ed6a
subsd (%r14), %xmm0
divsd 0x8(%r14), %xmm0
cvttsd2si %xmm0, %eax
leaq 0xc(%rsp), %r15
movl %eax, (%r15)
movl 0x40(%r14), %edx
decl %edx
movq %r15, %rdi
xorl %esi, %esi
callq 0x3a8de
addq $0x20, %r14
movq %r14, %rax
movq (%rax), %rax
movslq (%r15), %rcx
movsd (%rax,%rcx,8), %xmm0
movsd %xmm0, (%rbx)
movq %rbx, %rax
addq $0x28, %rsp
popq %rbx
popq %r12
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: test_regrule
Prediction test_regrule(Instanceptr data, void* model, void* parameters, double* posterior)
{
	/*!Last Changed 06.03.2005*/
	Regressionruleset r;
 Regressionruleptr rule;
 Prediction predicted;
	r = *((Regressionruleset*) model);
 rule = r.start;
 while (rule)
  {
   if (regression_rule_cover_instance(data, rule))
    {
     if (rule->leaftype == CONSTANTLEAF)
      {
       predicted.regvalue = rule->regressionvalue; 
       return predicted;
      }
     else
      {
       predicted.regvalue = linear_fit_value(rule->w, data); 
       return predicted;
      }
    }
   rule = rule->next;
  }
 if (r.leaftype == CONSTANTLEAF)
   predicted.regvalue = r.regressionvalue;
 else
   predicted.regvalue = linear_fit_value(r.w, data);
 return predicted;
}

// Assembly:
pushq %rbp
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
pushq %rax
movq %rsi, %r14
movq %rdi, %rbx
movq (%rdx), %r15
movq 0x10(%rdx), %r12
movq 0x18(%rdx), %r13
movl 0x20(%rdx), %ebp
movsd 0x28(%rdx), %xmm0
movsd %xmm0, (%rsp)
testq %r15, %r15
je 0x73de8
movq %r14, %rdi
movq %r15, %rsi
callq 0x75421
testl %eax, %eax
jne 0x73df9
movq 0x38(%r15), %r15
jmp 0x73dce
testl %ebp, %ebp
movsd (%rsp), %xmm0
je 0x73e0f
movq %r12, %rdi
movq %r13, %rsi
jmp 0x73e07
cmpl $0x0, 0x10(%r15)
je 0x73e25
movq (%r15), %rdi
movq 0x8(%r15), %rsi
movq %r14, %rdx
callq 0x76f0b
movsd %xmm0, (%rbx)
movq %rbx, %rax
addq $0x8, %rsp
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
popq %rbp
retq
movsd 0x18(%r15), %xmm0
jmp 0x73e0f
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: train_svmreg
void* train_svmreg(Instanceptr* trdata, Instanceptr *cvdata, void* parameters)
{
	/*!Last Changed 03.05.2005*/
 Partition dummyp;
	Svm_modelptr model;
	Svm_problem prob;
	Svm_parameterptr param;
	dummyp = get_two_class_partition();
	prepare_svm_problem(&prob, EPSILON_SVR, *trdata, dummyp);
	free_partition(dummyp);
	param = (Svm_parameter*) parameters;
 model = svm_train(prob, *param, 0);
	return model;
}

// Assembly:
pushq %r15
pushq %r14
pushq %rbx
subq $0xb0, %rsp
movq %rdx, %rbx
movq %rdi, %r14
leaq 0x78(%rsp), %r15
movq %r15, %rdi
xorl %eax, %eax
callq 0x55888
movq (%r14), %rdx
movq 0x10(%r15), %rax
movq %rax, 0x10(%rsp)
movups (%r15), %xmm0
movups %xmm0, (%rsp)
leaq 0x90(%rsp), %r14
movq %r14, %rdi
movl $0x3, %esi
callq 0x93fdc
movq 0x10(%r15), %rax
movq %rax, 0x10(%rsp)
movups (%r15), %xmm0
movups %xmm0, (%rsp)
callq 0x55a69
leaq 0x20(%rsp), %rdi
movl $0xb, %ecx
movq %rbx, %rsi
rep  movsq (%rsi), %es:(%rdi)
movups (%r14), %xmm0
movups 0x10(%r14), %xmm1
movups %xmm1, 0x10(%rsp)
movups %xmm0, (%rsp)
xorl %edi, %edi
callq 0x91556
addq $0xb0, %rsp
popq %rbx
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regression.c
// Function: test_svmreg
Prediction test_svmreg(Instanceptr data, void* model, void* parameters, double* posterior)
{
	/*!Last Changed 03.05.2005*/
	Svm_nodeptr node;
 Prediction predicted;
	Svm_modelptr m;
 double* dec_values;
 double y = give_regressionvalue(data);
	m = (Svm_modelptr) model;
	node = instance_to_svmnode(data);
 dec_values = safemalloc(sizeof(double), "test_svm", 7);
 svm_predict_values(m, node, dec_values);
 predicted.epsilonloss = epsilon_sensitive_loss(y, dec_values[0], get_parameter_f("svmepsilon"));
 safe_free(dec_values); 
	predicted.regvalue = svm_predict(m, node);
	safe_free(node);
 return predicted;
}

// Assembly:
pushq %r15
pushq %r14
pushq %r12
pushq %rbx
subq $0x18, %rsp
movq %rdx, %r14
movq %rsi, %r15
movq %rdi, %rbx
movq %rsi, %rdi
callq 0x2f35e
movsd %xmm0, 0x10(%rsp)
movq %r15, %rdi
callq 0x2ec9f
movq %rax, %r15
leaq 0x320e7(%rip), %rsi     # 0xa5fde
movl $0x8, %edi
movl $0x7, %edx
callq 0x3a0e1
movq %rax, %r12
movq %r14, %rdi
movq %r15, %rsi
movq %rax, %rdx
callq 0x925b3
movsd (%r12), %xmm0
movsd %xmm0, 0x8(%rsp)
leaq 0x31b1e(%rip), %rdi     # 0xa5a48
callq 0x549ba
movaps %xmm0, %xmm2
movsd 0x10(%rsp), %xmm0
movsd 0x8(%rsp), %xmm1
callq 0x47447
movsd %xmm0, 0x18(%rbx)
movq %r12, %rdi
callq 0x3a180
movq %r14, %rdi
movq %r15, %rsi
callq 0x93373
movsd %xmm0, (%rbx)
movq %r15, %rdi
callq 0x3a180
movq %rbx, %rax
addq $0x18, %rsp
popq %rbx
popq %r12
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regressionrule.c
// Function: write_nodetypes_regression_rule
void write_nodetypes_regression_rule(Regressionruleset r, char* st)
{
	/*!Last Changed 06.03.2005*/
	Regressionruleptr tmprule;
	Regressionconditionptr tmpcondition;
 sprintf(st, "%s", "");
	tmprule = r.start;
	while (tmprule)
	 {
		 tmpcondition = tmprule->start;
			while (tmpcondition)
			 {				 
				 if (tmpcondition->featureindex == LINEAR)
  				 sprintf(st, "%sL", st);
					else
						 if (tmpcondition->featureindex == QUADRATIC)
						   sprintf(st, "%sQ", st);
							else
								 sprintf(st, "%sU", st);
				 tmpcondition = tmpcondition->next;
			 }
			sprintf(st, "%s;", st);
		 tmprule = tmprule->next;
	 }
}

// Assembly:
pushq %rbp
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
pushq %rax
movb $0x0, (%rdi)
movq 0x40(%rsp), %r15
testq %r15, %r15
je 0x7401e
movq %rdi, %rbx
leaq 0x368ee(%rip), %r12     # 0xaa8b0
leaq 0x368eb(%rip), %r13     # 0xaa8b4
leaq 0x368dc(%rip), %rbp     # 0xaa8ac
movq 0x20(%r15), %r14
testq %r14, %r14
je 0x74001
movl (%r14), %eax
movq %r12, %rsi
cmpl $-0x3, %eax
je 0x73fe7
movq %r13, %rsi
cmpl $-0x2, %eax
cmoveq %rbp, %rsi
movq %rbx, %rdi
movq %rbx, %rdx
xorl %eax, %eax
callq 0x41b0
movq 0x20(%r14), %r14
jmp 0x73fd4
movq %rbx, %rdi
leaq 0x368bb(%rip), %rsi     # 0xaa8c6
movq %rbx, %rdx
xorl %eax, %eax
callq 0x41b0
movq 0x38(%r15), %r15
testq %r15, %r15
jne 0x73fd0
addq $0x8, %rsp
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
popq %rbp
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regressionrule.c
// Function: simplify_regression_ruleset
void simplify_regression_ruleset(Regressionruleset* r, Instanceptr data, int modelselectionmethod)
{
	/*!Last Changed 06.03.2005*/
	Regressionruleptr firstrule, deleted, tmprule, deletedbefore;
	double minerror, error;
	minerror = generalization_error_of_regression_ruleset(*r, data, modelselectionmethod);
	firstrule = r->start;
	deleted = r->end;
	while (deleted && deleted->next != firstrule)
	 {
		 tmprule = r->start;
			if (tmprule != deleted)
			 {
			  while (tmprule->next != deleted)
				   tmprule = tmprule->next;
			  deletedbefore = tmprule;
			 }
			else
				 deletedbefore = NULL;
			remove_regression_rule_after(r, deletedbefore, deleted);
			error = generalization_error_of_regression_ruleset(*r, data, modelselectionmethod);
			if (error > minerror)
				 add_regression_rule_after(r, deletedbefore, deleted);
			else
			 {
				 free_regression_rule(*deleted);
					safe_free(deleted);
				 minerror = error;
			 }
			deleted = deletedbefore;
	 }
}

// Assembly:
pushq %rbp
pushq %r15
pushq %r14
pushq %r13
pushq %r12
pushq %rbx
subq $0x58, %rsp
movl %edx, %ebx
movq %rsi, %r14
movq %rdi, %r15
movq 0x30(%rdi), %rax
movq %rax, 0x30(%rsp)
movupd (%rdi), %xmm0
movups 0x10(%rdi), %xmm1
movups 0x20(%rdi), %xmm2
movups %xmm2, 0x20(%rsp)
movups %xmm1, 0x10(%rsp)
movupd %xmm0, (%rsp)
movq %rsi, %rdi
movl %edx, %esi
callq 0x74192
movsd %xmm0, 0x50(%rsp)
movq 0x8(%r15), %rbp
testq %rbp, %rbp
je 0x74183
movq (%r15), %r13
movq 0x38(%rbp), %rax
cmpq %r13, %rax
je 0x74183
movq %rbp, %r12
movq (%r15), %rcx
cmpq %rbp, %rcx
je 0x740c3
movq %rcx, %rbp
movq 0x38(%rcx), %rcx
cmpq %r12, %rcx
jne 0x740b5
jmp 0x740c5
xorl %ebp, %ebp
decl 0x30(%r15)
je 0x740df
testq %rax, %rax
jne 0x740d4
movq %rbp, 0x8(%r15)
testq %rbp, %rbp
je 0x740ea
movq %rax, 0x38(%rbp)
jmp 0x740ed
xorpd %xmm0, %xmm0
movupd %xmm0, (%r15)
jmp 0x740ed
movq %rax, (%r15)
movq 0x30(%r15), %rax
movq %rax, 0x30(%rsp)
movupd (%r15), %xmm0
movups 0x10(%r15), %xmm1
movups 0x20(%r15), %xmm2
movups %xmm2, 0x20(%rsp)
movups %xmm1, 0x10(%rsp)
movupd %xmm0, (%rsp)
movq %r14, %rdi
movl %ebx, %esi
callq 0x74192
ucomisd 0x50(%rsp), %xmm0
jbe 0x74143
incl 0x30(%r15)
testq %rbp, %rbp
je 0x74166
movq 0x38(%rbp), %rax
movq %rax, 0x38(%r12)
movq %r12, 0x38(%rbp)
movq 0x38(%r12), %rax
jmp 0x74171
movl $0x9, %ecx
movq %rsp, %rdi
movq %r12, %rsi
rep  movsq (%rsi), %es:(%rdi)
movsd %xmm0, 0x50(%rsp)
callq 0x742e0
movq %r12, %rdi
callq 0x3a180
jmp 0x7417a
movq (%r15), %rax
movq %rax, 0x38(%r12)
movq %r12, (%r15)
testq %rax, %rax
jne 0x7417a
movq %r12, 0x8(%r15)
testq %rbp, %rbp
jne 0x7409d
addq $0x58, %rsp
popq %rbx
popq %r12
popq %r13
popq %r14
popq %r15
popq %rbp
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regressionrule.c
// Function: generalization_error_of_regression_ruleset
double generalization_error_of_regression_ruleset(Regressionruleset r, Instanceptr data, MODEL_SELECTION_TYPE modelselectionmethod)
{
	/*!Last Changed 04.03.2005*/
	double error;
	int complexity, size;
	error = mse_of_ruleset(r, data, &size);
	complexity = complexity_of_regression_ruleset(r);
	switch (modelselectionmethod)
	 {
	  case MODEL_SELECTION_CV :return error;
				                        break;
			case MODEL_SELECTION_AIC:return aic_squared_error(error, complexity, size);
				                        break;
			case MODEL_SELECTION_BIC:return bic_squared_error(error, complexity, size);
				                        break;
   default                 :printf(m1230, modelselectionmethod);
                            break;
	 }
	return error;
}

// Assembly:
pushq %rbp
pushq %r15
pushq %r14
pushq %rbx
subq $0x48, %rsp
movl %esi, %ebx
movq 0xa0(%rsp), %rax
movq %rax, 0x30(%rsp)
movaps 0x70(%rsp), %xmm0
movaps 0x80(%rsp), %xmm1
movaps 0x90(%rsp), %xmm2
movups %xmm2, 0x20(%rsp)
movups %xmm1, 0x10(%rsp)
movups %xmm0, (%rsp)
leaq 0x3c(%rsp), %rsi
callq 0x744f5
movsd %xmm0, 0x40(%rsp)
movq 0x70(%rsp), %r14
movl 0x90(%rsp), %r15d
xorl %ebp, %ebp
testq %r14, %r14
je 0x74202
movq %r14, %rdi
callq 0x74475
addl %eax, %ebp
movq 0x38(%r14), %r14
jmp 0x741ed
testl %r15d, %r15d
je 0x74219
leaq 0x61662(%rip), %rax     # 0xd5870
movq (%rax), %rax
addl 0x1c0(%rax), %ebp
jmp 0x7421b
incl %ebp
testl %ebx, %ebx
je 0x74279
cmpl $0x2, %ebx
je 0x74249
cmpl $0x1, %ebx
jne 0x74269
xorps %xmm1, %xmm1
cvtsi2sd %ebp, %xmm1
movl 0x3c(%rsp), %edi
movsd 0x40(%rsp), %xmm0
addq $0x48, %rsp
popq %rbx
popq %r14
popq %r15
popq %rbp
jmp 0x47841
xorps %xmm1, %xmm1
cvtsi2sd %ebp, %xmm1
movl 0x3c(%rsp), %edi
movsd 0x40(%rsp), %xmm0
addq $0x48, %rsp
popq %rbx
popq %r14
popq %r15
popq %rbp
jmp 0x47c88
leaq 0x3b8ec(%rip), %rdi     # 0xafb5c
movl %ebx, %esi
xorl %eax, %eax
callq 0x4030
movsd 0x40(%rsp), %xmm0
addq $0x48, %rsp
popq %rbx
popq %r14
popq %r15
popq %rbp
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regressionrule.c
// Function: add_regression_rule_after
void add_regression_rule_after(Regressionruleset* r, Regressionruleptr before, Regressionruleptr inserted)
{
	/*!Last Changed 04.03.2005*/
	r->rulecount++;
	if (before == NULL)
	 {
		 inserted->next = r->start;
		 r->start = inserted;
	 }
	else
	 {
		 inserted->next = before->next;
		 before->next = inserted;
	 }
	if (inserted->next == NULL)
			r->end = inserted;
}

// Assembly:
incl 0x30(%rdi)
testq %rsi, %rsi
je 0x742cb
movq 0x38(%rsi), %rax
movq %rax, 0x38(%rdx)
movq %rdx, 0x38(%rsi)
movq 0x38(%rdx), %rax
jmp 0x742d5
movq (%rdi), %rax
movq %rax, 0x38(%rdx)
movq %rdx, (%rdi)
testq %rax, %rax
je 0x742db
retq
movq %rdx, 0x8(%rdi)
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regressionrule.c
// Function: free_regression_rule
void free_regression_rule(Regressionrule rule)
{
	/*!Last Changed 27.03.2005*/
	/*!Last Changed 02.03.2005*/
	Regressionconditionptr tmp, next;
	tmp = rule.start;
	while (tmp)
	 {
		 next = tmp->next;
			if (in_list(tmp->featureindex, 2, LINEAR, QUADRATIC))
			 {
				 deallocate(tmp->leftcenter);
				 deallocate(tmp->rightcenter);
			 }
			safe_free(tmp);
			tmp = next;
	 }
	if (rule.leaftype == LINEARLEAF)
		 matrix_free(rule.w);
}

// Assembly:
pushq %r15
pushq %r14
pushq %rbx
leaq 0x20(%rsp), %r14
movq 0x20(%r14), %rbx
testq %rbx, %rbx
je 0x74335
movq 0x20(%rbx), %r15
movl (%rbx), %edi
movl $0x2, %esi
movl $0xfffffffe, %edx       # imm = 0xFFFFFFFE
movl $0xfffffffd, %ecx       # imm = 0xFFFFFFFD
xorl %eax, %eax
callq 0x3aa8c
testl %eax, %eax
je 0x74325
movq 0x10(%rbx), %rdi
callq 0x2ff55
movq 0x18(%rbx), %rdi
callq 0x2ff55
movq %rbx, %rdi
callq 0x3a180
movq %r15, %rbx
testq %r15, %r15
jne 0x742f3
cmpl $0x1, 0x10(%r14)
jne 0x7434d
movq (%r14), %rdi
movq 0x8(%r14), %rsi
popq %rbx
popq %r14
popq %r15
jmp 0x3ed51
popq %rbx
popq %r14
popq %r15
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regressionrule.c
// Function: generalization_error_of_regression_rule
double generalization_error_of_regression_rule(Regressionruleptr rule, Instanceptr data, MODEL_SELECTION_TYPE modelselectionmethod)
{
	/*!Last Changed 06.03.2005*/
	double error;
	int complexity, size;
	error = mse_of_rule(rule, data, &size);
	complexity = complexity_of_regression_rule(rule);
	switch (modelselectionmethod)
	 {
	  case MODEL_SELECTION_CV :return error;
				                        break;
			case MODEL_SELECTION_AIC:return aic_squared_error(error, complexity, size);
				                        break;
			case MODEL_SELECTION_BIC:return bic_squared_error(error, complexity, size);
				                        break;
   default                 :printf(m1230, modelselectionmethod);
                            break;
	 }
	return error;
}

// Assembly:
pushq %r14
pushq %rbx
subq $0x18, %rsp
movl %edx, %ebx
movq %rdi, %r14
leaq 0xc(%rsp), %rdx
callq 0x743d7
movsd %xmm0, 0x10(%rsp)
movq %r14, %rdi
callq 0x74475
testl %ebx, %ebx
je 0x743c9
cmpl $0x2, %ebx
je 0x7439f
cmpl $0x1, %ebx
jne 0x743b9
cvtsi2sd %eax, %xmm1
movl 0xc(%rsp), %edi
movsd 0x10(%rsp), %xmm0
addq $0x18, %rsp
popq %rbx
popq %r14
jmp 0x47841
cvtsi2sd %eax, %xmm1
movl 0xc(%rsp), %edi
movsd 0x10(%rsp), %xmm0
addq $0x18, %rsp
popq %rbx
popq %r14
jmp 0x47c88
leaq 0x3b79c(%rip), %rdi     # 0xafb5c
movl %ebx, %esi
xorl %eax, %eax
callq 0x4030
movsd 0x10(%rsp), %xmm0
addq $0x18, %rsp
popq %rbx
popq %r14
retq
// File: /workspace/github_c_makefile_star2_O3/olcaytaner[P]Isell/regressionrule.c
// Function: mse_of_rule
double mse_of_rule(Regressionruleptr c, Instanceptr list, int* covered)
{
	/*!Last Changed 02.03.2005*/
	Instanceptr tmp;
	double result = 0;
	tmp = list;
	*covered = 0;
	while (tmp)
	 {
		 if (regression_rule_cover_instance(tmp, c))
			 {
				 (*covered)++;
					result += instance_regression_error(c->w, c->regressionvalue, tmp, c->leaftype);
			 }
		 tmp = tmp->next;
	 }
	return result / (*covered);
}

// Assembly:
movl $0x0, (%rdx)
testq %rsi, %rsi
je 0x74468
pushq %r15
pushq %r14
pushq %r12
pushq %rbx
pushq %rax
movq %rdx, %rbx
movq %rsi, %r14
movq %rdi, %r15
xorpd %xmm1, %xmm1
movsd %xmm1, (%rsp)
movq %r15, %r12
movq 0x20(%r12), %r12
testq %r12, %r12
je 0x74423
movq %r14, %rdi
movq %r12, %rsi
callq 0x7554c
testl %eax, %eax
jne 0x74403
movsd (%rsp), %xmm1
jmp 0x74447
incl (%rbx)
movsd 0x18(%r15), %xmm0
movl 0x10(%r15), %ecx
movq (%r15), %rdi
movq 0x8(%r15), %rsi
movq %r14, %rdx
callq 0x76f96
movsd (%rsp), %xmm1
addsd %xmm0, %xmm1
movq 0x10(%r14), %r14
testq %r14, %r14
jne 0x743fb
xorps %xmm0, %xmm0
cvtsi2sdl (%rbx), %xmm0
divsd %xmm0, %xmm1
addq $0x8, %rsp
popq %rbx
popq %r12
popq %r14
popq %r15
jmp 0x74470
movsd 0x318a0(%rip), %xmm1    # 0xa5d10
movapd %xmm1, %xmm0
retq