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libagf is a library of variable-bandwidth kernel estimators for statistical classification, PDF estimation, and interpolation/non-linear regression using both Gaussian kernels and k-nearest-neighbours. Statistical classification allows the use of a pre-trained model for considerable speed gains. Also included are clustering algorithms. It includes command line executables as well as easy-to-use libraries.

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2011-11-28 07:20 Back to release list
0.9.4

Todo excepto las rutinas de I/O ha sido basado en plantilla. Con excepción de los utilizados en rutinas externas, los tipos de variables en las rutinas principales ahora son controlados con typedefs global, con cada clase de variable de un tipo diferente. Ahora sólo se admiten diferentes métricas en las rutinas donde tiene sentido: KNN clasificación e interpolación de KNN. Las funciones ahora requieren un puntero a la métrica deseada. La rutina nfold ahora soporta interpolación. Tenga en cuenta que esto es todavía no bien probado (si en absoluto).
Everything except the I/O routines has been templated. With the exception of those used in external routines, variable types in the main routines are now controlled with global typedefs, with each class of variable having a different type. Different metrics are now only supported in the routines where they make sense: KNN classification and KNN interpolation. The functions now require a pointer to the desired metric. The nfold routine now supports interpolation. Note that this is still not well tested (if at all).

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