Description: The target variable is a fundamental concept in model optimization, especially in the fields of machine learning and statistics. It refers to the variable that a model seeks to predict or optimize, acting as the outcome or output that is desired to be achieved. In the context of a predictive model, the target variable can be continuous, such as the price of a house, or categorical, such as classifying an email as ‘spam’ or ‘not spam’. The precise identification and definition of the target variable are crucial, as it determines the direction of the analysis and the type of algorithms that will be used. Additionally, the quality of the data feeding the model and its relationship with the target variable will directly influence the accuracy and effectiveness of the model. In summary, the target variable is the central axis around which the modeling process revolves, guiding feature selection, performance evaluation, and interpretation of the results obtained.