This data was used in the machine learning analysis of the Cosmic Microwave Background data in: https://github.com/IndiraOcampo/CMB_ML_based_model_selection.git and https://dx.doi.org/10.1088/1475-7516/2025/02/004 The objective is to train a neural network architecture on the different polarization modes (TT, TE, EE and joint) to perform model selection between the standard cosmological model, ΛCDM and a modified gravity model, Hu-Sawicki f(R). The first row corresponds to the multipole moment "\ell" and the remaining ones correspond to the different components of the Cl's angular power spectrum, for the different values of f_R0 (the MoG deviation parameter). While f_R0 = 10^-6 is a reasonable value that still agrees with observations, f_R0 = 0 corresponds to the ΛCDM model. Finally, our aim is to apply SHAP to perform feature importance (interpretability) in our results.