CONCEPTUAL MODEL FOR GENDER PREDICTION BASED ON USER INPUT

The present study examines an approach to the synthesis of a conceptual model for gender prediction based on user input. The predictive capability of the model is grounded in statistical differences observed within specific datasets and in the applicability of a machine-learning classification model. The predictive analysis is governed by a set of parameters, including language, the specifications of the peripheral input device, sample size, and biological indicators. It should be noted that reliable classification of a user's gender is a function of predefined key indicators.