pyclustering 0.10.1

pyclustering 0.10.0.1 library is a collection of clustering algorithms, oscillatory networks, etc.

GENERAL CHANGES:

• The library is distributed under BSD-3-Clause library. See: https://github.com/annoviko/pyclustering/issues/517

• C++ pyclustering can be built using CMake. See: https://github.com/annoviko/pyclustering/issues/603

• Supported dumping and loading for DBSCAN algorithm via pickle (Python: pyclustering.cluster.dbscan). See: https://github.com/annoviko/pyclustering/issues/650

• Package installer resolves all required dependencies automatically. See: https://github.com/annoviko/pyclustering/issues/647

• Introduced human-readable error for genetic clustering algorithm in case of non-normalized data (Python: pyclustering.cluster.ga). See: https://github.com/annoviko/pyclustering/issues/597

• Optimized windows implementation parallel_for and parallel_for_each by using pyclustering::parallel instead of PPL that affects all algorithms which use these functions (C++: pyclustering::parallel). See: https://github.com/annoviko/pyclustering/issues/642

• Optimized parallel_for algorithm for short cycles that affects all algorithms which use parallel_for (C++: pyclustering::parallel). See: https://github.com/annoviko/pyclustering/issues/642

• Introduced kstep parameter for elbow algorithm to use custom K search steps (Python: pyclustering.cluster.elbow, C++: pyclustering::cluster::elbow). See: https://github.com/annoviko/pyclustering/issues/489

• Introduced p_step parameter for parallel_for function (C++: pyclustering::parallel). See: https://github.com/annoviko/pyclustering/issues/640

• Optimized python implementation of K-Medoids algorithm (Python: pyclustering.cluster.kmedoids). See: https://github.com/annoviko/pyclustering/issues/526

• C++ pyclustering CLIQUE interface returns human-readable errors (Python: pyclustering.cluster.clique). See: https://github.com/annoviko/pyclustering/issues/635 See: https://github.com/annoviko/pyclustering/issues/634

• Introduced metric parameter for X-Means algorithm to use custom metric for clustering (Python: pyclustering.cluster.xmeans; C++ pyclustering::clst::xmeans). See: https://github.com/annoviko/pyclustering/issues/619

• Introduced alpha and beta probabilistic bounds for MNDL splitting criteria for X-Means algorithm (Python: pyclustering.cluster.xmeans; C++: pyclustering::clst::xmeans). See: https://github.com/annoviko/pyclustering/issues/624

CORRECTED MAJOR BUGS:

• Corrected bug with a command python3 -m pyclustering.tests that was using the current folder to find tests to run (Python: pyclustering). See: https://github.com/annoviko/pyclustering/issues/648

• Corrected bug with Elbow algorithm where kmax is not used to calculate K (Python: pyclustering.cluster.elbow; C++: pyclustering::clst::elbow). See: https://github.com/annoviko/pyclustering/issues/639

• Corrected implementation of K-Medians (PAM) algorithm that is aligned with original algorithm (Python: pyclustering.cluster.kmedoids; C++: pyclustering::clst::kmedoids). See: https://github.com/annoviko/pyclustering/issues/503

• Corrected literature references that were for K-Medians (PAM) implementation (Python: pyclustering.cluster.kmedoids). See: https://github.com/annoviko/pyclustering/pull/572

• Corrected bug when K-Medoids updates input parameter initial_medoids that were provided to the algorithm (Python: pyclustering.cluster.kmedoids). See: https://github.com/annoviko/pyclustering/issues/630

• Corrected bug with Euclidean distance when numpy is used (Python: pyclustering.utils.metric). See: https://github.com/annoviko/pyclustering/issues/625

• Corrected bug with Minkowski distance when numpy is used (Python: pyclustering.utils.metric). See: https://github.com/annoviko/pyclustering/issues/626

• Corrected bug with Gower distance when numpy calculation is used and data shape is bigger than 1 (Python: pyclustering.utils.metric). See: https://github.com/annoviko/pyclustering/issues/627

• Corrected MNDL splitting criteria for X-Means algorithm (Python: pyclustering.cluster.xmeans; C++: pyclustering::clst::xmeans). See: https://github.com/annoviko/pyclustering/issues/623