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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 | ||
Reporter | SergeyB | View Status | public | ||||
Assigned To | SergeyB | ||||||
Priority | normal | Resolution | implemented | Platform | |||
Status | resolved | OS | |||||
Projection | none | OS Version | |||||
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 | ||||||
Description |
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. |
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Steps To Reproduce | |||||||
Additional Information | |||||||
Programming language | Unspecified | ||||||
Attached Files | |||||||
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