20 :
CSGObject(), vw_version(
"5.1"), v_length(4)
25 void CVwEnvironment::init()
uint32_t vw_size_t
vw_size_t typedef to work across platforms
float64_t initial_t
Initial value of t
float64_t weighted_examples
Weighted examples
bool random_weights
Whether to use random weights
void set_stride(vw_size_t new_stride)
float64_t min_label
Smallest label seen
int64_t example_number
Example number
float32_t l1_regularization
Level of L1 regularization
vw_size_t num_bits
log_2 of the number of features
float32_t eta
Learning rate
float64_t max_label
Largest label seen
float32_t update_sum
Sum of updates
bool exact_adaptive_norm
Whether exact norm is used for adaptive learning
float32_t power_t
t power value while updating
Class SGObject is the base class of all shogun objects.
float64_t weighted_labels
Weighted labels
vw_size_t ngram
ngrams to generate
float32_t eta_decay_rate
Decay rate of eta per pass
bool ignore_some
Whether some namespaces are ignored
vw_size_t num_passes
Number of passes
vw_size_t stride
Number of elements in weight vector per feature
vw_size_t skips
Skips in ngrams
vw_size_t mask
Mask used for hashing
vw_size_t total_features
Total number of features
all of classes and functions are contained in the shogun namespace
vw_size_t thread_bits
log_2 of the number of threads
float32_t initial_weight
Initial value of all elements in weight vector
float64_t weighted_unlabeled_examples
Weighted unlabelled examples
vw_size_t thread_mask
Mask used by regressor for learning
bool adaptive
Whether adaptive learning is used
vw_size_t passes_complete
Number of passes complete
float64_t sum_loss
Sum of losses