diff options
author | Chris Dyer <cdyer@cs.cmu.edu> | 2011-03-17 22:46:35 -0400 |
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committer | Chris Dyer <cdyer@cs.cmu.edu> | 2011-03-17 22:46:35 -0400 |
commit | f8f499c69cba280894d1ddf974a9038ac2211fc6 (patch) | |
tree | 6f835eb7675b205324920e5cef17c3a06b9d5ff8 /training/online_optimizer.h | |
parent | b6e699cb65f3f6e603434a7e702f8d46df4881ec (diff) |
freeze features, including penalty
Diffstat (limited to 'training/online_optimizer.h')
-rw-r--r-- | training/online_optimizer.h | 17 |
1 files changed, 12 insertions, 5 deletions
diff --git a/training/online_optimizer.h b/training/online_optimizer.h index 312aabae..61d62a37 100644 --- a/training/online_optimizer.h +++ b/training/online_optimizer.h @@ -2,6 +2,7 @@ #define _ONL_OPTIMIZE_H_ #include <tr1/memory> +#include <set> #include <string> #include <cmath> #include "sparse_vector.h" @@ -56,8 +57,12 @@ class OnlineOptimizer { public: virtual ~OnlineOptimizer(); OnlineOptimizer(const std::tr1::shared_ptr<LearningRateSchedule>& s, - size_t batch_size) - : N_(batch_size),schedule_(s),k_() {} + size_t batch_size, + const std::vector<int>& frozen_feats = std::vector<int>()) + : N_(batch_size),schedule_(s),k_() { + for (int i = 0; i < frozen_feats.size(); ++i) + frozen_.insert(frozen_feats[i]); + } void ResetEpoch() { k_ = 0; ResetEpochImpl(); } void UpdateWeights(const SparseVector<double>& approx_g, int max_feat, SparseVector<double>* weights) { ++k_; @@ -69,6 +74,7 @@ class OnlineOptimizer { virtual void ResetEpochImpl(); virtual void UpdateWeightsImpl(const double& eta, const SparseVector<double>& approx_g, int max_feat, SparseVector<double>* weights) = 0; const size_t N_; // number of training instances per batch + std::set<int> frozen_; // frozen (non-optimizing) features private: std::tr1::shared_ptr<LearningRateSchedule> schedule_; @@ -78,8 +84,9 @@ class OnlineOptimizer { class CumulativeL1OnlineOptimizer : public OnlineOptimizer { public: CumulativeL1OnlineOptimizer(const std::tr1::shared_ptr<LearningRateSchedule>& s, - size_t training_instances, double C) : - OnlineOptimizer(s, training_instances), C_(C), u_() {} + size_t training_instances, double C, + const std::vector<int>& frozen) : + OnlineOptimizer(s, training_instances, frozen), C_(C), u_() {} protected: void ResetEpochImpl() { u_ = 0; } @@ -87,7 +94,7 @@ class CumulativeL1OnlineOptimizer : public OnlineOptimizer { u_ += eta * C_ / N_; (*weights) += eta * approx_g; for (int i = 1; i < max_feat; ++i) - ApplyPenalty(i, weights); + if (frozen_.count(i) == 0) ApplyPenalty(i, weights); } private: |