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openGPMP
Open Source Mathematics Package
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openGPMP
Open Source Mathematics Package
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| Cgpmp::ml::Activation | Activation Methods |
| Cgpmp::Arith< T > | Arithmetic Basics |
| ▼Cgpmp::ml::AutoEncoder | A simple implementation of a vanilla autoencoder |
| Cgpmp::ml::ConcreteAutoEncoder | ConcreteAutoEncoder class, a derived class from AutoEncoder |
| Cgpmp::ml::ContractiveAutoEncoder | ContractiveAutoEncoder class, a derived class from AutoEncoder |
| Cgpmp::ml::DenoisingAutoEncoder | DenoisingAutoEncoder class, a derived class from AutoEncoder |
| Cgpmp::ml::FullAutoEncoder | FullAutoEncoder class, a derived class from AutoEncoder |
| Cgpmp::ml::MDLAutoEncoder | MDLAutoEncoder Minimal Description Length class, a derived class from AutoEncoder |
| Cgpmp::ml::RecurrentAutoEncoder | RecurrentAutoEncoder class, a derived class from AutoEncoder |
| Cgpmp::ml::SparseAutoEncoder | SparseAutoEncoder class, a derived class from AutoEncoder |
| Cgpmp::ml::VariationalAutoEncoder | VariationalAutoEncoder class, a derived class from AutoEncoder |
| CBall | |
| Cgpmp::Basics | Arithmetic Operations |
| Cgpmp::ml::BayesBernoulli | |
| Cgpmp::ml::BayesClf | Bayes Classifier Class based on assumptions of independence |
| Cgpmp::ml::BayesGauss | |
| Cgpmp::ml::BayesMultiNom | |
| CBayesMutliNom | |
| CBNN | Bayesian Neural Network class |
| CCamera | |
| Cgpmp::stats::CDF | Class providing methods for computing cumulative distribution functions (CDFs) |
| CCheckerboard | |
| Cgpmp::Cipher | |
| Cgpmp::accl::CLmtx | OpenCL GPU Matrix operations wrapper class |
| Cgpmp::Comb | A class providing various combinatorial functions and algorithms |
| Cgpmp::accl::CUDAmtx | Features CUDA GPU acceleration methods related to matrix operations |
| Cgpmp::core::DataTable | |
| Cgpmp::stats::Describe | A class providing methods for descriptive statistics |
| Cgpmp::linalg::DGEMM | Class for performing matrix multiplication on double type arrays |
| Cgpmp::Differential | Calculus Class with methods pertaining to basic operations |
| CEdge | |
| Cgpmp::linalg::Eigen | Class for computing eigenvalues of a matrix |
| Cgpmp::EuclideanDivision | |
| Cgpmp::Factorization | |
| Cgpmp::optim::Func | A class containing various utility functions and optimization methods |
| Cgpmp::GCDS | |
| Cgpmp::Graph | |
| Cgpmp::stats::HypothesisTest | A class for conducting various statistical hypothesis tests |
| Cgpmp::linalg::IGEMM | Class for performing matrix multiplication on int type arrays |
| Cgpmp::ml::Kfold | Represents a k-fold cross-validation utility |
| Cgpmp::ml::KNN | Represents a K Nearest Neighbors (KNN) classifier |
| Cgpmp::ml::KohonenNet | Kohonen Neural Network Cluster Class |
| Cgpmp::ml::layer | |
| Cgpmp::core::rndm::LCG | Linear Congruential Generator |
| Cgpmp::ml::LinearRegression | |
| Cgpmp::linalg::LinSys | Class for solving linear systems and performing matrix operations |
| Cgpmp::Logarithms | |
| Cgpmp::core::Logger | |
| Cgpmp::ml::LogReg | Represents a Logistic Regression classifier |
| Cgpmp::linalg::Matrix< Type > | Matrix and Scalar operations |
| Cgpmp::core::Misc | A class containing miscellaneous utility functions |
| Cgpmp::linalg::Mtx | Mtx class offers matrix arithmetic operations. Some methods are element-wise while others make use of grouping and unrolling |
| Cgpmp::linalg::mtx< T > | Matrix struct |
| Cgpmp::ml::neuron | |
| Cgpmp::NumericalAnalysis | |
| ▼Cobject | |
| Cpygpmp.arithmetic.arithmetic.Basics | |
| Cpygpmp.calculus.calculus.Differential | |
| Cpygpmp.calculus.calculus.Term | |
| Cpygpmp.core.core.DataTable | |
| Cpygpmp.core.core.Logger | |
| Cpygpmp.core.core.Misc | |
| Cpygpmp.core.core.TypeCast | |
| Cpygpmp.linalg.linalg.Mtx | |
| Cpygpmp.ml.ml.LinearRegression | |
| Cpygpmp.nt.nt.Basics | |
| Cpygpmp.nt.nt.Cipher | |
| Cpygpmp.nt.nt.Factorization | |
| Cpygpmp.nt.nt.Logarithms | |
| Cpygpmp.nt.nt.PrimalityGen | |
| Cpygpmp.nt.nt.PrimalityTest | |
| Cpygpmp.nt.nt.RC4 | |
| Cgpmp::stats::PDF | Class representing Probability Distribution Functions (PDFs) |
| Cgpmp::PrimalityGen | |
| Cgpmp::PrimalityTest | |
| Cgpmp::ml::PrimaryMLP | Primary Multi-Layer Perceptron Class |
| Cgpmp::stats::ProbDist | |
| CQuantile | |
| Cgpmp::optim::QuasiNewton | Class implementing Quasi-Newton optimization methods |
| Cgpmp::RC4 | |
| Cgpmp::nt::RC5 | RC5 encryption and decryption class |
| CRC6 | Class implementing the RC6 cipher algorithm |
| Cgpmp::nt::RedPike | Class for encryption and decryption using the RedPike algorithm |
| Cgpmp::ml::Regularize | |
| Cgpmp::stats::Resampling | A class providing various resampling methods for statistical analysis |
| Cgpmp::ml::SecondaryMLP< T > | Secondary Multi-Layer Perceptron Class making use of the Linear Algebra module |
| Cgpmp::linalg::SGEMM | Class for performing matrix multiplication on float type arrays |
| Cgpmp::Squares | |
| Cgpmp::ml::Stats | |
| Cgpmp::ml::SVC | Support Vector Classifier (SVC) for binary classification using Stochastic Gradient Descent |
| Cgpmp::linalg::SVD | |
| Cgpmp::linalg::Tensor | Represents a 3D tensor with basic operations |
| Cgpmp::Term | Represents a term in a polynomial |
| Cgpmp::core::ThreadDispatch | A class that provides a function to dispatch a function call to a thread pool and return a future object for obtaining the result |
| Cgpmp::core::ThreadPool | |
| Cgpmp::ml::Trainers | Training Algorithms |
| Cgpmp::core::TypeCast |
1.9.1