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FIX handle properly null weights in SVC #27763

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FIX handle properly null weights in SVC #27763

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1142cbd
FIX handle properly null weights in SVC
glemaitre Nov 10, 2023
d6b78f3
rename remove_zeros_weight to remove_negative_and_null_weights
glemaitre Nov 10, 2023
fbf8925
FIX return correct support indices with null weights
glemaitre Nov 10, 2023
bacf4d7
fix more
glemaitre Nov 11, 2023
34baa18
iter
glemaitre Nov 14, 2023
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1 change: 1 addition & 0 deletions sklearn/svm/_libsvm_sparse.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -169,6 +169,7 @@ def libsvm_sparse_train (int n_features,
blas_functions.dot = _dot[double]
# call svm_train, this does the real work
cdef int fit_status = 0

with nogil:
model = svm_csr_train(problem, param, &fit_status, &blas_functions)

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39 changes: 20 additions & 19 deletions sklearn/svm/src/liblinear/linear.cpp
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Expand Up @@ -2424,26 +2424,27 @@ static int train_one(const problem *prob, const parameter *param, double *w, dou
//
// Remove zero weighed data as libsvm and some liblinear solvers require C > 0.
//
static void remove_zero_weight(problem *newprob, const problem *prob)
static void remove_negative_and_null_weights(problem *newprob, const problem *prob)
{
int i;
int l = 0;
for(i=0;i<prob->l;i++)
if(prob->W[i] > 0) l++;
*newprob = *prob;
newprob->l = l;
newprob->x = Malloc(feature_node*,l);
newprob->y = Malloc(double,l);
newprob->W = Malloc(double,l);
int sample_idx;
int n_samples = prob->l;
int n_positive_samples = 0;
for(sample_idx=0; sample_idx < n_samples; sample_idx++)
if(prob->W[sample_idx] > 0) n_positive_samples++;

int j = 0;
for(i=0;i<prob->l;i++)
if(prob->W[i] > 0)
{
newprob->x[j] = prob->x[i];
newprob->y[j] = prob->y[i];
newprob->W[j] = prob->W[i];
j++;
*newprob = *prob;
newprob->l = n_positive_samples;
newprob->x = Malloc(feature_node*, n_positive_samples);
newprob->y = Malloc(double, n_positive_samples);
newprob->W = Malloc(double, n_positive_samples);

int subsample_idx = 0;
for(sample_idx=0; sample_idx < n_samples; sample_idx++)
if(prob->W[sample_idx] > 0) {
newprob->x[subsample_idx] = prob->x[sample_idx];
newprob->y[subsample_idx] = prob->y[sample_idx];
newprob->W[subsample_idx] = prob->W[sample_idx];
subsample_idx++;
}
}

Expand All @@ -2453,7 +2454,7 @@ static void remove_zero_weight(problem *newprob, const problem *prob)
model* train(const problem *prob, const parameter *param, BlasFunctions *blas_functions)
{
problem newprob;
remove_zero_weight(&newprob, prob);
remove_negative_and_null_weights(&newprob, prob);
prob = &newprob;
int i,j;
int l = prob->l;
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