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Update liblinear to 2.50

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dmiller
2026-01-28 22:23:52 +00:00
parent c1d16550dc
commit 59bb6e4e4e
5 changed files with 66 additions and 14 deletions
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27
liblinear/linear.cpp
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@@ -1064,6 +1064,21 @@ static int solve_l2r_l1l2_svc(const problem *prob, const parameter *param, doubl
info("Objective value = %lf\n",v/2);
info("nSV = %d\n",nSV);
// Reconstruct w from the primal-dual relationship w=sum(\alpha_i y_i x_i)
// This may reduce the weight density. Some zero weights become non-zeros
// due to the numerical update w <- w + (alpha[i] - alpha_old) y_i x_i.
if (param->w_recalc)
{
for(i=0; i<w_size; i++)
w[i] = 0;
for(i=0; i<l; i++)
{
feature_node * const xi = prob->x[i];
if(alpha[i] > 0)
sparse_operator::axpy(y[i]*alpha[i], xi, w);
}
}
delete [] QD;
delete [] alpha;
delete [] y;
@@ -2194,11 +2209,14 @@ static int partition(feature_node *nodes, int low, int high)
return index;
}
// rearrange nodes so that nodes[:k] contains nodes with the k smallest values.
// rearrange nodes so that
// nodes[i] <= nodes[k] for all i < k
// nodes[k] <= nodes[j] for all j > k
// low and high are the bounds of the index range during the rearranging process
static void quick_select_min_k(feature_node *nodes, int low, int high, int k)
{
int pivot;
if(low == high)
if(low == high || high < k)
return;
pivot = partition(nodes, low, high);
if(pivot == k)
@@ -3718,6 +3736,11 @@ const char *check_parameter(const problem *prob, const parameter *param)
&& param->solver_type != L2R_L2LOSS_SVR)
return "Initial-solution specification supported only for solvers L2R_LR, L2R_L2LOSS_SVC, and L2R_L2LOSS_SVR";
if(param->w_recalc == true
&& param->solver_type != L2R_L2LOSS_SVC_DUAL
&& param->solver_type != L2R_L1LOSS_SVC_DUAL)
return "Recalculating w in the end is only for dual solvers for L2-regularized L1/L2-loss SVM";
return NULL;
}