Here is a list of all data types members with links to the data types they belong to:

- c -

• C : gpmp::ml::SVC
• caesar() : gpmp::Cipher , pygpmp.nt.nt.Cipher
• calculate_bhhh_matrix() : gpmp::optim::QuasiNewton
• calculate_centroid() : gpmp::optim::Func
• calculate_coeffecient() : gpmp::ml::LinearRegression , pygpmp.ml.ml.LinearRegression
• calculate_constant() : gpmp::ml::LinearRegression , pygpmp.ml.ml.LinearRegression
• calculate_gradient() : gpmp::optim::QuasiNewton
• calculate_gradient_difference() : gpmp::optim::QuasiNewton
• calculate_midpoint() : gpmp::optim::Func
• calculate_range() : gpmp::optim::Func
• calculate_search_direction() : gpmp::optim::QuasiNewton
• calculateEuclideanDistance() : gpmp::ml::KNN
• Camera() : Camera
• carmichael_num() : gpmp::PrimalityTest , pygpmp.nt.nt.PrimalityTest
• cauchy() : gpmp::stats::CDF , gpmp::stats::PDF , Quantile
• centerx() : Checkerboard
• centerz() : Checkerboard
• chain_rule() : gpmp::Differential , pygpmp.calculus.calculus.Differential
• chebyshevIneq() : gpmp::ml::Stats
• Checkerboard() : Checkerboard
• chi_square_test() : gpmp::stats::HypothesisTest
• chi_squared() : gpmp::stats::CDF , gpmp::stats::PDF
• chiSquared() : Quantile
• chiSquareTest() : gpmp::ml::Stats
• choose_random_neighbor() : gpmp::Graph
• chromatic_number() : gpmp::Graph
• chunking() : gpmp::EuclideanDivision
• cipolla() : gpmp::Squares
• circular_block_bootstrap() : gpmp::stats::Resampling
• class_log_prior : gpmp::ml::BayesClf , gpmp::ml::BayesMultiNom
• class_probs : gpmp::ml::BayesBernoulli , gpmp::ml::BayesClf , gpmp::ml::BayesGauss , gpmp::ml::BayesMultiNom
• classify() : gpmp::ml::KohonenNet , gpmp::ml::LogReg
• clt() : gpmp::stats::Describe
• coeff : gpmp::ml::LinearRegression , pygpmp.ml.ml.LinearRegression
• coefficient : gpmp::Term , pygpmp.calculus.calculus.Term
• color : Ball
• cols : gpmp::linalg::Matrix< Type >
• combination() : gpmp::Comb
• combinations() : gpmp::Comb
• compositions() : gpmp::Comb
• compress() : gpmp::Graph
• compute() : gpmp::RC4 , pygpmp.nt.nt.RC4
• compute_loss() : BNN , gpmp::ml::SVC
• compute_miller_rabin() : gpmp::PrimalityTest , pygpmp.nt.nt.PrimalityTest
• computeHouseholderReflection() : gpmp::linalg::SVD
• computeSVD() : gpmp::linalg::SVD
• concatenate() : gpmp::linalg::Matrix< Type >
• ConcreteAutoEncoder() : gpmp::ml::ConcreteAutoEncoder
• condition : gpmp::core::ThreadPool
• ConfidenceInterval() : gpmp::stats::ProbDist
• connected_components() : gpmp::Graph
• CONST : gpmp::nt::RedPike
• constant : gpmp::ml::LinearRegression , pygpmp.ml.ml.LinearRegression
• constantApproximation() : gpmp::NumericalAnalysis
• contractive_weight : gpmp::ml::ContractiveAutoEncoder
• ContractiveAutoEncoder() : gpmp::ml::ContractiveAutoEncoder
• contramean_harmonic() : gpmp::ml::Stats
• convert() : gpmp::core::TypeCast , pygpmp.core.core.TypeCast
• correlation() : gpmp::ml::Stats
• corruption_level : gpmp::ml::DenoisingAutoEncoder
• cost_function() : gpmp::ml::LogReg
• covariance() : gpmp::ml::Stats
• create() : Checkerboard
• cross_val_score() : gpmp::ml::SVC
• csv_read() : gpmp::core::DataTable , pygpmp.core.core.DataTable
• csv_read_new() : gpmp::core::DataTable
• csv_write() : gpmp::core::DataTable , pygpmp.core.core.DataTable
• cubic_fit() : gpmp::optim::Func
• cubic_interpolation() : gpmp::optim::Func
• cubicApproximation() : gpmp::NumericalAnalysis