NNBMSS: a Novel and Fast Method for Model Structure Selection

Amaury Lendasse, Kallin Khan, Edward Ratner
2021 ESANN 2021 proceedings   unpublished
In this paper, we present a new method to perform model structure selection. This proposed method can be used to select the complexity of any continuous regression method. We also present an asymptotic mathematical proof of the proposed method and the new method is illustrated on a benchmark. Compared to the well-known 10-fold Cross-Validation, the computational time associated to our new method is approximately divided by a factor 8 as illustrated on the benchmark.
doi:10.14428/esann/2021.es2021-9 fatcat:wdz3ivxowren7ooekkoqdssiey