This page contains three files, including Int_div_mod2, Int_div_mod3 and Fourier_series_regression, which are the code for the paper "Classification of integers based on residue classes via modern deep learning algorithms". All these three scripts incorporate data generation processes.
In particular, the "Int_div_mod2" and "Int_div_mod3" scripts outline a comprehensive examination of diverse deep learning architectures following distinct approaches to feature engineering. The outcome of this experimentation yielded results that were not only instinctive but also easily comprehensible. For a more in-depth analysis, we encourage readers to refer to the dedicated "Results" and "Discussion" sections in paper. Furthermore, for those inclined, our code can be readily modified and employed for personalized testing and exploration. This flexibility allows interested individuals to tailor the code to their specific requirements and objectives.
Furthermore, the paper incorporates a comprehensive exploration of the Fourier series regression method using ordinary least squares (OLS). This technique is extensively elucidated in Section 4.4 of the paper. The script "Fourier_series_regression" provides comprehensive implementations, and it can be easily modified for interested readers to explore different mod p classification problems.
This python script contains all the testings of deep neual networks on mod 2 problem, including all the feature engineering listed in Table (1)(a) with the same order.
This python script contains all the testings of deep neural networks on mod 3 problem, including all the feature engineering listed in Table (1)(b) with the same order.
This python script contains the implementation of Fourier series regression on mod 3 and mod 7 problems describled in Section 4.4.