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[optimization] Adding learning rate to lazy sparse update in stochastic gradient descent

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Al
2016-01-12 11:02:12 -05:00
parent 79f2b7c192
commit 622dc354e7
3 changed files with 17 additions and 15 deletions
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4
src/logistic_regression_trainer.c
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@@ -118,7 +118,7 @@ bool logistic_regression_trainer_train_batch(logistic_regression_trainer_t *self
goto exit_matrices_created;
}
if (self->lambda > 0.0 && !stochastic_gradient_descent_sparse_regularize_weights(self->weights, self->batch_columns, self->last_updated, self->iters, self->lambda)) {
if (self->lambda > 0.0 && !stochastic_gradient_descent_sparse_regularize_weights(self->weights, self->batch_columns, self->last_updated, self->iters, self->lambda, self->gamma_0)) {
log_error("Error regularizing weights\n");
goto exit_matrices_created;
}
@@ -145,7 +145,7 @@ bool logistic_regression_trainer_finalize(logistic_regression_trainer_t *self) {
if (self == NULL) return false;
if (self->lambda > 0.0) {
return stochastic_gradient_descent_sparse_finalize_weights(self->weights, self->last_updated, self->iters, self->lambda);
return stochastic_gradient_descent_sparse_finalize_weights(self->weights, self->last_updated, self->iters, self->lambda, self->gamma_0);
}
return true;