Reverberant shear wave field elastography (R-SWE) is an image modality that evaluates tissue stiffness by creating a reverberant shear wave field in all directions of the medium. This implementation facilitates the estimation of the shear wave speed (SWS), ergo the viscoelasticity of the tissue. Its feasibility has been validated in breast, liver, corneas and plantar tissue. Nevertheless, the calculus of the SWS is verified as long as a uniform field is generated. Current method uses the coefficient of determination (R2) derived of a curve fitting as a quality parameter of reverberation. In this work, the uniformity phenomenon in reveberant fields is studied through the extraction and analysis of statistical estimators used in electromagnetic fields with their equivalency in acoustic waves to implement machine learning classifiers of uniform reverberant fields such as Logistic Regression, LDA, Lineal SVM and Gaussian SVM. The models detect uniform regions with accuracies of 0.749, 0.746, 0.715 and 0.811, respectively.