- _ -

_data : xmm::Matrix< T >

- a -

absolute_regularization : xmm::ClassParameters< GMM > , xmm::ClassParameters< HMM >
AllocationBlockSize : xmm::Phrase
alpha : xmm::SingleClassHMM
alpha_h : xmm::SingleClassHMM
alpha_seq_ : xmm::SingleClassHMM
angle : xmm::Ellipse

- b -

beta : xmm::SingleClassGMM
beta_ : xmm::SingleClassHMM
beta_seq_ : xmm::SingleClassHMM
bimodal : xmm::SharedParameters
bimodal_ : xmm::GaussianDistribution , xmm::Phrase , xmm::TrainingSet

- c -

callback_ : xmm::Attribute< T > , xmm::Attribute< std::vector< std::string > > , xmm::Attribute< std::vector< T > >
callbacks_ : xmm::EventGenerator< EventType >
cancel_required_ : xmm::Model< SingleClassModel, ModelType >
cancel_training_ : xmm::SingleClassProbabilisticModel
centers : xmm::KMeans
changed : xmm::AttributeBase , xmm::ClassParameters< ModelType > , xmm::ClassParameters< GMM > , xmm::ClassParameters< HMM > , xmm::ClassParameters< KMeans >
class_parameters_ : xmm::Configuration< ModelType >
clusters : xmm::ClassParameters< KMeans >
column_names : xmm::Phrase , xmm::SharedParameters , xmm::TrainingSet
components : xmm::SingleClassGMM
configuration : xmm::KMeans , xmm::Model< SingleClassModel, ModelType >
covariance : xmm::GaussianDistribution
covariance_determinant_ : xmm::GaussianDistribution
covariance_determinant_input_ : xmm::GaussianDistribution
covariance_mode : xmm::ClassParameters< GMM > , xmm::ClassParameters< HMM > , xmm::GaussianDistribution
current_index_ : xmm::CircularBuffer< T, channels >
current_regularization : xmm::SingleClassGMM

- d -

data : xmm::Matrix< T >
data_ : xmm::CircularBuffer< T, channels > , xmm::Phrase
DEFAULT_MAX_ITERATIONS : xmm::KMeans
dimension : xmm::GaussianDistribution , xmm::Phrase , xmm::SharedParameters , xmm::TrainingSet
dimension_input : xmm::GaussianDistribution , xmm::Phrase , xmm::SharedParameters , xmm::TrainingSet
distances : xmm::Results< KMeans >

- e -

em_algorithm_max_iterations : xmm::SharedParameters
em_algorithm_min_iterations : xmm::SharedParameters
em_algorithm_percent_chg : xmm::SharedParameters
empty_ : xmm::Phrase
epsilon_sequence_ : xmm::SingleClassHMM
errorType_ : xmm::JsonException
event_mutex_ : xmm::Model< SingleClassModel, ModelType >
events : xmm::Phrase
exit_likelihood : xmm::ClassResults< HMM >
exit_probabilities_ : xmm::SingleClassHMM
exit_ratio : xmm::ClassResults< HMM >
exit_transition : xmm::HierarchicalHMM

- f -

forward_initialized_ : xmm::HierarchicalHMM , xmm::SingleClassHMM
frontier_v1_ : xmm::HierarchicalHMM
frontier_v2_ : xmm::HierarchicalHMM
full_ : xmm::CircularBuffer< T, channels >

- g -

gamma_sequence_ : xmm::SingleClassHMM
gamma_sequence_per_mixture_ : xmm::SingleClassHMM
gamma_sum_ : xmm::SingleClassHMM
gamma_sum_per_mixture_ : xmm::SingleClassHMM
gaussians : xmm::ClassParameters< GMM > , xmm::ClassParameters< HMM >

- h -

height : xmm::Ellipse
hierarchical : xmm::ClassParameters< HMM >

- i -

initialization_mode : xmm::KMeans
input_length_ : xmm::Phrase
instant_likelihood : xmm::ClassResults< ModelType > , xmm::ClassResults< HMM >
instant_likelihoods : xmm::Results< ModelType >
instant_normalized_likelihoods : xmm::Results< ModelType >
inverse_covariance_ : xmm::GaussianDistribution
inverse_covariance_input_ : xmm::GaussianDistribution
is_hierarchical_ : xmm::SingleClassHMM
is_joining_ : xmm::Model< SingleClassModel, ModelType >
is_training_ : xmm::Model< SingleClassModel, ModelType > , xmm::SingleClassProbabilisticModel
iterations : xmm::TrainingEvent

- l -

label : xmm::Phrase , xmm::SingleClassProbabilisticModel , xmm::TrainingEvent
labels_ : xmm::TrainingSet
length_ : xmm::CircularBuffer< T, channels > , xmm::Phrase
likeliest : xmm::Results< ModelType > , xmm::Results< KMeans >
likeliest_state : xmm::ClassResults< HMM >
likelihood_buffer_ : xmm::SingleClassProbabilisticModel
likelihood_window : xmm::SharedParameters
limit_max_ : xmm::Attribute< T > , xmm::Attribute< std::vector< std::string > > , xmm::Attribute< std::vector< T > >
limit_min_ : xmm::Attribute< T > , xmm::Attribute< std::vector< std::string > > , xmm::Attribute< std::vector< T > >
log_likelihood : xmm::ClassResults< ModelType > , xmm::ClassResults< HMM > , xmm::TrainingEvent

- m -

max_iterations : xmm::ClassParameters< KMeans >
max_length_ : xmm::Phrase
mean : xmm::GaussianDistribution
mixture_coeffs : xmm::SingleClassGMM
model : xmm::TrainingEvent
models : xmm::Model< SingleClassModel, ModelType >
models_still_training_ : xmm::Model< SingleClassModel, ModelType >
multiClass_regression_estimator : xmm::Configuration< ModelType >
multithreading : xmm::Configuration< ModelType >

- n -

- o -

output_covariance : xmm::ClassResults< ModelType > , xmm::ClassResults< HMM > , xmm::GaussianDistribution , xmm::Results< ModelType >
output_length_ : xmm::Phrase
output_values : xmm::ClassResults< ModelType > , xmm::ClassResults< HMM > , xmm::Results< ModelType >
own_memory_ : xmm::Phrase , xmm::TrainingSet
ownData : xmm::Matrix< T >

- p -

parameters : xmm::SingleClassGMM , xmm::SingleClassHMM
phrase : xmm::PhraseEvent
phrases_ : xmm::TrainingSet
previous_alpha_ : xmm::SingleClassHMM
previous_beta_ : xmm::SingleClassHMM
prior : xmm::HierarchicalHMM , xmm::SingleClassHMM
progress : xmm::ClassResults< HMM >
progression : xmm::TrainingEvent

- r -

regression_estimator : xmm::ClassParameters< HMM >
relative_distance_threshold : xmm::ClassParameters< KMeans >
relative_regularization : xmm::ClassParameters< GMM > , xmm::ClassParameters< HMM >
results : xmm::GMM , xmm::HierarchicalHMM , xmm::KMeans , xmm::SingleClassGMM , xmm::SingleClassHMM

- s -

shared_parameters : xmm::KMeans , xmm::Model< SingleClassModel, ModelType > , xmm::SingleClassProbabilisticModel
size_ : xmm::Attribute< std::vector< std::string > > , xmm::Attribute< std::vector< T > >
smoothed_likelihoods : xmm::Results< ModelType >
smoothed_log_likelihoods : xmm::Results< ModelType >
smoothed_normalized_likelihoods : xmm::Results< ModelType >
states : xmm::ClassParameters< HMM > , xmm::SingleClassHMM
status : xmm::TrainingEvent
sub_training_sets_ : xmm::TrainingSet

- t -

training_events : xmm::Model< SingleClassModel, ModelType > , xmm::SingleClassProbabilisticModel
training_mutex_ : xmm::SingleClassProbabilisticModel
training_status : xmm::SingleClassProbabilisticModel
training_threads_ : xmm::Model< SingleClassModel, ModelType >
transition : xmm::HierarchicalHMM , xmm::SingleClassHMM
transition_mode : xmm::ClassParameters< HMM >
type : xmm::PhraseEvent

- v -

value_ : xmm::Attribute< T > , xmm::Attribute< std::vector< std::string > > , xmm::Attribute< std::vector< T > >

- w -

width : xmm::Ellipse
window_maxindex_ : xmm::SingleClassHMM
window_minindex_ : xmm::SingleClassHMM
window_normalization_constant_ : xmm::SingleClassHMM

- x -

x : xmm::Ellipse

- y -

y : xmm::Ellipse

XMM - Probabilistic Models for Motion Recognition and Mapping

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