openGPMP
Open Source Mathematics Package
- r -
R2() :
gpmp::ml::Stats
r_sqrd() :
gpmp::ml::LinearRegression
,
pygpmp.ml.ml.LinearRegression
rademacher() :
gpmp::stats::CDF
,
gpmp::stats::PDF
radius() :
gpmp::Graph
rand() :
gpmp::linalg::mtx< T >
rand_init() :
gpmp::ml::PrimaryMLP
rand_int() :
gpmp::ml::PrimaryMLP
rand_real() :
gpmp::ml::PrimaryMLP
randn() :
gpmp::linalg::mtx< T >
random_search() :
gpmp::optim::Func
range() :
gpmp::ml::Stats
,
gpmp::stats::Describe
rank_data() :
gpmp::stats::Describe
rayleigh_iter() :
gpmp::linalg::Eigen
RC5() :
gpmp::nt::RC5
RC6() :
RC6
recurr_fwd() :
gpmp::ml::RecurrentAutoEncoder
RecurrentAutoEncoder() :
gpmp::ml::RecurrentAutoEncoder
reflect() :
gpmp::optim::Func
regula_falsi() :
gpmp::optim::Func
relu() :
gpmp::ml::Activation
relu_derivative() :
gpmp::ml::Activation
reparameterize() :
gpmp::ml::VariationalAutoEncoder
return_coeffecient() :
gpmp::ml::LinearRegression
,
pygpmp.ml.ml.LinearRegression
return_constant() :
gpmp::ml::LinearRegression
,
pygpmp.ml.ml.LinearRegression
RMS() :
gpmp::ml::Stats
rotl() :
gpmp::nt::RC5
,
gpmp::nt::RedPike
,
RC6
rotr() :
gpmp::nt::RC5
,
gpmp::nt::RedPike
,
RC6
run() :
gpmp::ml::PrimaryMLP
runs_test() :
gpmp::stats::HypothesisTest
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