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DBSCAN* [6] [7] is a variation that treats border points as noise, and this way achieves a fully deterministic result as well as a more consistent statistical interpretation of density-connected components. The quality of DBSCAN depends on the distance measure used in the function regionQuery(P,ε).
Binary-code compatibility (binary compatible or object-code compatible) is a property of a computer system, meaning that it can run the same executable code, typically machine code for a general-purpose computer central processing unit (CPU), that another computer system can run.
The R package "dbscan" includes a C++ implementation of OPTICS (with both traditional dbscan-like and ξ cluster extraction) using a k-d tree for index acceleration for Euclidean distance only. Python implementations of OPTICS are available in the PyClustering library and in scikit-learn. HDBSCAN* is available in the hdbscan library.
A complete ABI, such as the Intel Binary Compatibility Standard (iBCS), [1] allows a program from one operating system supporting that ABI to run without modifications on any other such system, provided that necessary shared libraries are present, and similar prerequisites are fulfilled.
Only 32-bit drivers were included in this release. 3.5 (1996–10): Supports double-byte character set (DBCS), and accommodated the use of File data source names (DSNs). The Microsoft Access driver was released in an RISC version for use on Alpha platforms for Windows 95/98 and Windows NT 3.51 and later operating systems.
MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. Although MATLAB is intended primarily for numeric computing, an optional toolbox uses the MuPAD symbolic engine allowing access to symbolic computing abilities.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
FEATool Multiphysics is a Matlab GUI toolbox for finite element FEM and PDE multiphysics simulations. FEniCS Project is a collection of project for automated solutions to PDEs. Hermes is a C++ library of advanced adaptive finite element algorithms to solve PDEs and multiphysics coupled problems. Fityk is a curve fitting and data-analysis ...