Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:

[detail level 1234]

▼Cmltk::metrics::dist::BaseMatrix
Cmltk::metrics::dist::DistanceMatrix< DistanceFunc >
Cmltk::datasets::BlobsPair
Cmltk::validation::CrossValidation	Structure to manage cross validation
Cmltk::Data< T >	Wrapper for the dataset data
Cmltk::Data< double >
Cmltk::Data< T >
▼Cmltk::metrics::dist::DistanceMetric< T >	Base functor class for the implementation of new metrics metrics
Cmltk::metrics::dist::Euclidean< T >
▼Cmltk::metrics::dist::DistanceMetric< double >
Cmltk::metrics::dist::Euclidean< double >
Cmltk::metrics::dist::AdditiveSymmetric< T >
Cmltk::metrics::dist::Average< T >
Cmltk::metrics::dist::AverageL1Linf< T >
Cmltk::metrics::dist::AvgManhattan< T >
Cmltk::metrics::dist::Bhattacharyya< T >
Cmltk::metrics::dist::Canberra< T >
Cmltk::metrics::dist::Chebyshev< T >
Cmltk::metrics::dist::Chord< T >
Cmltk::metrics::dist::Clark< T >
Cmltk::metrics::dist::Cosine< T >
Cmltk::metrics::dist::Dice< T >
Cmltk::metrics::dist::Divergence< T >
Cmltk::metrics::dist::Euclidean< T >	Functor for the computation of the euclidean metrics between two points
Cmltk::metrics::dist::Hassanat< T >
Cmltk::metrics::dist::Hellinger< T >
Cmltk::metrics::dist::Jaccard< T >
Cmltk::metrics::dist::Jeffreys< T >
Cmltk::metrics::dist::JensenDifference< T >
Cmltk::metrics::dist::JensenShannon< T >
Cmltk::metrics::dist::KDivergence< T >
Cmltk::metrics::dist::KullbackLeibler< T >
Cmltk::metrics::dist::KumarJohnson< T >
Cmltk::metrics::dist::Lorentzian< T >
Cmltk::metrics::dist::Manhattan< T >
Cmltk::metrics::dist::Matusita< T >
Cmltk::metrics::dist::MaxSymmetric< T >
Cmltk::metrics::dist::MinSymmetric< T >
Cmltk::metrics::dist::Neyman< T >
Cmltk::metrics::dist::NonIntersection< T >
Cmltk::metrics::dist::Pearson< T >
Cmltk::metrics::dist::ProbabilisticSymmetric< T >
Cmltk::metrics::dist::Sorensen< T >
Cmltk::metrics::dist::Squared< T >
Cmltk::metrics::dist::SquaredChiSquared< T >
Cmltk::metrics::dist::SquaredChord< T >
Cmltk::metrics::dist::SquaredEuclidean< T >
Cmltk::metrics::dist::Taneja< T >
Cmltk::metrics::dist::Topsoe< T >
Cmltk::DSM< T >
▼Cstd::exception	STL class
►Cstd::runtime_error	STL class
CGnuplotException	A C++ interface to gnuplot
Cmltk::featselect::FeatureSelection< T >
▼Cmltk::featselect::FeatureSelection< double >
Cmltk::featselect::AOS< T >
Cmltk::featselect::Fisher< T >
Cmltk::featselect::Golub< T >
Cmltk::featselect::RFE< T >
CGnuplot
Cmltk::featselect::AOS< T >::Hash
Cmltk::featselect::AOS< T >::Heap
Cmltk::classifier::int_dll
Cmltk::Kernel< T >	Class for the kernel computations
Cmltk::Kernel< double >
Cmltk::Kernel< T >
▼Cmltk::Learner< T >
►Cmltk::clusterer::Clusterer< double >
Cmltk::clusterer::KMeans< T, Callable >	Wrapper for the implementation of the K-Means clustering algorithm
▼Cmltk::Learner< T >
►Cmltk::classifier::Classifier< T >
►Cmltk::classifier::DualClassifier< double >
Cmltk::classifier::IMADual< T >
►Cmltk::classifier::PrimalClassifier< double >
Cmltk::classifier::IMAp< T >	Wrapper for the implementation of the Incremental Margin Algorithm primal
Cmltk::classifier::IMApFixedMargin< T >	Wrapper for the implementation of the Incremental Margin Algorithm primal with fixed margin
Cmltk::classifier::KNNClassifier< T, Callable >	Wrapper for the implementation of the K-Nearest Neighbors classifier algorithm
►Cmltk::classifier::DualClassifier< T >
Cmltk::classifier::OneVsAll< T >	Wrapper for the implementation of the one vs all multi class classification algorithm
Cmltk::classifier::OneVsOne< T >	Wrapper for the implementation of the one vs one multi class classification algorithm
Cmltk::classifier::PerceptronDual< T >	Wrapper for the implementation of the Perceptron dual algorithm
Cmltk::classifier::PerceptronFixedMarginDual< T >	Wrapper for the implementation of the Perceptron dual with fixed margin algorithm
Cmltk::classifier::SMO< T >
►Cmltk::classifier::PrimalClassifier< T >
Cmltk::classifier::BalancedPerceptron< T >
Cmltk::classifier::OneVsAll< T >	Wrapper for the implementation of the one vs all multi class classification algorithm
Cmltk::classifier::OneVsOne< T >	Wrapper for the implementation of the one vs one multi class classification algorithm
Cmltk::classifier::PerceptronFixedMarginPrimal< T >	Wrapper for the implementation of the Perceptron primal with fixed margin algorithm
Cmltk::classifier::PerceptronPrimal< T >	Wrapper for the implementation of the Perceptron primal algorithm
Cmltk::ensemble::AdaBoostClassifier< T >
Cmltk::ensemble::AutoWeightedVoting< T >
Cmltk::ensemble::BaggingClassifier< T >
Cmltk::ensemble::PerceptronCommittee< T >
Cmltk::ensemble::VotingClassifier< T >
Cmltk::clusterer::Clusterer< T, Callable >
►Cmltk::ensemble::Ensemble< T >	Namespace for ensemble methods
Cmltk::ensemble::AdaBoostClassifier< T >
Cmltk::ensemble::AutoWeightedVoting< T >
Cmltk::ensemble::BaggingClassifier< T >
Cmltk::ensemble::PerceptronCommittee< T >
Cmltk::ensemble::VotingClassifier< T >
►Cmltk::regressor::Regressor< T >
►Cmltk::regressor::PrimalRegressor< double >
Cmltk::regressor::KNNRegressor< T, Callable >	Wrapper for the implementation of the K-Nearest Neighbors regression algorithm
Cmltk::regressor::LMSPrimal< T >	Wrapper for the implementation of the Least Mean Square primal algorithm
Cmltk::regressor::DualRegressor< T >
Cmltk::regressor::PrimalRegressor< T >
Cmltk::OverSampling< T, Callable >	Base class for the implementation of over sampling methods
▼Cmltk::OverSampling< double, metrics::dist::Euclidean< double > >
Cmltk::BorderlineSMOTEOne< T, Callable >	Functor for the implementation of the Borderline SMOTE 1 over sampling algorithm
Cmltk::SMOTE< T, Callable >	Functor for the implementation of the SMOTE over sampling algorithm
Cmltk::Point< T, Rep >	Wrapper for the point data
Cmltk::Point< double >
Cmltk::Point< size_t >
Cmltk::Point< T >
Cmltk::datasets::RegPair
Cmltk::RSM< T >
Cmltk::featselect::AOS< T >::select_gamma
Cmltk::featselect::AOS< T >::select_weight
▼Cmltk::Solution
Cmltk::validation::ValidationReport	Solution for the validation of a ML method
Cmltk::Statistics< T >
Cmltk::synced_stream	A helper class to synchronize printing to an output stream by different threads
Cmltk::ThreadPool	A C++17 thread pool class. The user submits tasks to be executed into a queue. Whenever a thread becomes available, it pops a task from the queue and executes it. Each task is automatically assigned a future, which can be used to wait for the task to finish executing and/or obtain its eventual return value
Cmltk::Timer	Wrapper for the implementation of a simple timer
Cmltk::timer	A helper class to measure execution time for benchmarking purposes
Cmltk::validation::TrainTestPair< T >	A struct representing a pair with training and test data
Cmltk::visualize::Visualization< T >	Class for data visualization