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|ID||Category||Severity||Reproducibility||Date Submitted||Last Update|
|0000692||[ALGLIB] Interpolation||feature||have not tried||2017-04-18 16:58||2017-04-18 16:59|
|ETA||none||Fixed in Version||3.11.0||Product Version|
|Target Version||3.11.0||Product Build|
|Summary||0000692: IMPLEMENTED: fitting minimum circumscribed, minimum zone, maximum inscribed circles to N-dimensional data|
Implemented fitting minimum circumscribed (MCC), minimum zone (MZC), maximum inscribed (MIC) circles/spheres to N-dimensional data.
Two algorithms are provided:
* robust (although less efficient) NLC one, based on ALGLIB nonlinearly constrained solver. This algorithm shows good convergence properties.
* fast inexact SLP (sequential linear programming) one, based on ALGLIB linearly constrained solver.
NOTE: SLP approach to MCC/MZC/MIC is recommended by many authors; however, empirical testing demonstrated that linearization of the problem often breaks down near true solution (validated in MATLAB; it is deficiency of linearization, not solver used for such model). Thus, SLP solver often fails to converge to more than 3-5 digits of precision. However, it is 10-20 times faster than NLC, and on some problems it works good enough. That's why we included it as non-standard option.
|Steps To Reproduce|
|There are no notes attached to this issue.|
|2017-04-18 16:58||SergeyB||New Issue|
|2017-04-18 16:58||SergeyB||Status||new => assigned|
|2017-04-18 16:58||SergeyB||Assigned To||=> SergeyB|
|2017-04-18 16:58||SergeyB||Programming language||=> Unspecified|
|2017-04-18 16:59||SergeyB||Status||assigned => resolved|
|2017-04-18 16:59||SergeyB||Fixed in Version||=> 3.11.0|
|2017-04-18 16:59||SergeyB||Resolution||open => implemented|
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