bob.learn.em
2.1.8
User guide
Python API
bob.learn.em
»
Index
Index
A
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B
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C
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D
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E
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F
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G
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H
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I
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J
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K
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L
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M
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N
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P
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R
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S
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T
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U
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V
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W
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X
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Y
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Z
A
acc_d_a1 (bob.learn.em.JFATrainer attribute)
acc_d_a2 (bob.learn.em.JFATrainer attribute)
acc_fnormij_wij (bob.learn.em.IVectorTrainer attribute)
acc_nij (bob.learn.em.IVectorTrainer attribute)
acc_nij_wij2 (bob.learn.em.IVectorTrainer attribute)
acc_snormij (bob.learn.em.IVectorTrainer attribute)
acc_u_a1 (bob.learn.em.ISVTrainer attribute)
(bob.learn.em.JFATrainer attribute)
acc_u_a2 (bob.learn.em.ISVTrainer attribute)
(bob.learn.em.JFATrainer attribute)
acc_v_a1 (bob.learn.em.JFATrainer attribute)
acc_v_a2 (bob.learn.em.JFATrainer attribute)
alpha (bob.learn.em.MAP_GMMTrainer attribute)
average_min_distance (bob.learn.em.KMeansTrainer attribute)
B
bob.learn.em
module
C
clear_maps() (bob.learn.em.PLDABase method)
(bob.learn.em.PLDAMachine method)
compute_gamma() (bob.learn.em.PLDABase method)
compute_likelihood() (bob.learn.em.EMPCATrainer method)
(bob.learn.em.KMeansTrainer method)
(bob.learn.em.MAP_GMMTrainer method)
(bob.learn.em.ML_GMMTrainer method)
compute_log_like_const_term() (bob.learn.em.PLDABase method)
compute_log_likelihood() (bob.learn.em.PLDAMachine method)
compute_log_likelihood_point_estimate() (bob.learn.em.PLDABase method)
create_from_dict() (bob.learn.em.GMMMachine class method)
(bob.learn.em.ISVBase class method)
D
d (bob.learn.em.JFABase attribute)
E
e_step() (bob.learn.em.EMPCATrainer method)
(bob.learn.em.ISVTrainer method)
(bob.learn.em.IVectorTrainer method)
(bob.learn.em.KMeansTrainer method)
(bob.learn.em.MAP_GMMTrainer method)
(bob.learn.em.ML_GMMTrainer method)
(bob.learn.em.PLDATrainer method)
e_step_d() (bob.learn.em.JFATrainer method)
e_step_u() (bob.learn.em.JFATrainer method)
e_step_v() (bob.learn.em.JFATrainer method)
EMPCATrainer (class in bob.learn.em)
enroll() (bob.learn.em.ISVTrainer method)
(bob.learn.em.JFATrainer method)
(bob.learn.em.PLDATrainer method)
estimate_ux() (bob.learn.em.JFAMachine method)
estimate_x() (bob.learn.em.JFAMachine method)
F
f (bob.learn.em.PLDABase attribute)
finalize() (bob.learn.em.PLDATrainer method)
finalize_d() (bob.learn.em.JFATrainer method)
finalize_u() (bob.learn.em.JFATrainer method)
finalize_v() (bob.learn.em.JFATrainer method)
first_order_statistics (bob.learn.em.KMeansTrainer attribute)
forward_ux() (bob.learn.em.JFAMachine method)
G
g (bob.learn.em.PLDABase attribute)
Gaussian (class in bob.learn.em)
get_add_gamma() (bob.learn.em.PLDABase method)
(bob.learn.em.PLDAMachine method)
get_add_log_like_const_term() (bob.learn.em.PLDABase method)
(bob.learn.em.PLDAMachine method)
get_config() (in module bob.learn.em)
get_gamma() (bob.learn.em.PLDABase method)
(bob.learn.em.PLDAMachine method)
get_log_like_const_term() (bob.learn.em.PLDABase method)
(bob.learn.em.PLDAMachine method)
gmm_shape_from_dict() (bob.learn.em.GMMMachine static method)
gmm_statistics (bob.learn.em.MAP_GMMTrainer attribute)
(bob.learn.em.ML_GMMTrainer attribute)
GMMMachine (class in bob.learn.em)
GMMStats (class in bob.learn.em)
H
has_gamma() (bob.learn.em.PLDABase method)
(bob.learn.em.PLDAMachine method)
has_log_like_const_term() (bob.learn.em.PLDABase method)
(bob.learn.em.PLDAMachine method)
I
init_f_method (bob.learn.em.PLDATrainer attribute)
init_g_method (bob.learn.em.PLDATrainer attribute)
init_sigma_method (bob.learn.em.PLDATrainer attribute)
initialization_method (bob.learn.em.KMeansTrainer attribute)
initialize() (bob.learn.em.EMPCATrainer method)
(bob.learn.em.ISVTrainer method)
(bob.learn.em.IVectorTrainer method)
(bob.learn.em.JFATrainer method)
(bob.learn.em.KMeansTrainer method)
(bob.learn.em.MAP_GMMTrainer method)
(bob.learn.em.ML_GMMTrainer method)
(bob.learn.em.PLDATrainer method)
is_similar_to() (bob.learn.em.Gaussian method)
(bob.learn.em.JFABase method)
(bob.learn.em.JFAMachine method)
(bob.learn.em.PLDABase method)
(bob.learn.em.PLDAMachine method)
(bob.learn.em.PLDATrainer method)
ISVBase (class in bob.learn.em)
ISVMachine (class in bob.learn.em)
ISVTrainer (class in bob.learn.em)
IVectorMachine (class in bob.learn.em)
IVectorTrainer (class in bob.learn.em)
J
jfa_base (bob.learn.em.JFAMachine attribute)
JFABase (class in bob.learn.em)
JFAMachine (class in bob.learn.em)
JFATrainer (class in bob.learn.em)
K
KMeansMachine (class in bob.learn.em)
KMeansTrainer (class in bob.learn.em)
L
linear_scoring() (in module bob.learn.em)
load() (bob.learn.em.Gaussian method)
(bob.learn.em.JFABase method)
(bob.learn.em.JFAMachine method)
(bob.learn.em.PLDABase method)
(bob.learn.em.PLDAMachine method)
log_likelihood (bob.learn.em.PLDAMachine attribute)
log_likelihood() (bob.learn.em.Gaussian method)
(bob.learn.em.JFAMachine method)
log_likelihood_() (bob.learn.em.Gaussian method)
log_likelihood_ratio() (bob.learn.em.PLDAMachine method)
M
m_step() (bob.learn.em.EMPCATrainer method)
(bob.learn.em.ISVTrainer method)
(bob.learn.em.IVectorTrainer method)
(bob.learn.em.KMeansTrainer method)
(bob.learn.em.MAP_GMMTrainer method)
(bob.learn.em.ML_GMMTrainer method)
(bob.learn.em.PLDATrainer method)
m_step_d() (bob.learn.em.JFATrainer method)
m_step_u() (bob.learn.em.JFATrainer method)
m_step_v() (bob.learn.em.JFATrainer method)
MAP_GMMTrainer (class in bob.learn.em)
mean (bob.learn.em.Gaussian attribute)
ML_GMMTrainer (class in bob.learn.em)
module
bob.learn.em
mu (bob.learn.em.PLDABase attribute)
N
n_samples (bob.learn.em.PLDAMachine attribute)
P
plda_base (bob.learn.em.PLDAMachine attribute)
PLDABase (class in bob.learn.em)
PLDAMachine (class in bob.learn.em)
PLDATrainer (class in bob.learn.em)
Process() (bob.learn.em.ThreadPool static method)
R
relevance_factor (bob.learn.em.MAP_GMMTrainer attribute)
reset_accumulators() (bob.learn.em.IVectorTrainer method)
(bob.learn.em.KMeansTrainer method)
resize() (bob.learn.em.Gaussian method)
(bob.learn.em.JFABase method)
(bob.learn.em.PLDABase method)
S
save() (bob.learn.em.Gaussian method)
(bob.learn.em.JFABase method)
(bob.learn.em.JFAMachine method)
(bob.learn.em.PLDABase method)
(bob.learn.em.PLDAMachine method)
set_variance_thresholds() (bob.learn.em.Gaussian method)
shape (bob.learn.em.Gaussian attribute)
(bob.learn.em.JFABase attribute)
(bob.learn.em.JFAMachine attribute)
(bob.learn.em.PLDABase attribute)
(bob.learn.em.PLDAMachine attribute)
sigma (bob.learn.em.PLDABase attribute)
sigma2 (bob.learn.em.EMPCATrainer attribute)
supervector_length (bob.learn.em.JFABase attribute)
(bob.learn.em.JFAMachine attribute)
T
ThreadPool (class in bob.learn.em)
to_dict() (bob.learn.em.GMMMachine static method)
(bob.learn.em.GMMStats static method)
(bob.learn.em.ISVBase static method)
(bob.learn.em.ISVMachine static method)
(bob.learn.em.IVectorMachine static method)
(bob.learn.em.KMeansMachine static method)
train() (in module bob.learn.em)
train_jfa() (in module bob.learn.em)
U
u (bob.learn.em.JFABase attribute)
ubm (bob.learn.em.JFABase attribute)
update_dict() (bob.learn.em.GMMMachine method)
(bob.learn.em.ISVBase method)
(bob.learn.em.ISVMachine method)
(bob.learn.em.IVectorMachine method)
use_sum_second_order (bob.learn.em.PLDATrainer attribute)
V
v (bob.learn.em.JFABase attribute)
variance (bob.learn.em.Gaussian attribute)
variance_threshold (bob.learn.em.PLDABase attribute)
variance_thresholds (bob.learn.em.Gaussian attribute)
W
w_sum_xit_beta_xi (bob.learn.em.PLDAMachine attribute)
weighted_sum (bob.learn.em.PLDAMachine attribute)
X
x (bob.learn.em.JFAMachine attribute)
Y
y (bob.learn.em.JFAMachine attribute)
Z
z (bob.learn.em.JFAMachine attribute)
z_first_order (bob.learn.em.PLDATrainer attribute)
z_second_order (bob.learn.em.PLDATrainer attribute)
z_second_order_sum (bob.learn.em.PLDATrainer attribute)
zeroeth_order_statistics (bob.learn.em.KMeansTrainer attribute)