Which Selection tool provides criteria based on R-square or chi-square for selecting variables?

The selection tool that provides criteria based on R-square or chi-square for selecting variables is the Variable Selection tool. This tool evaluates potential predictor variables to determine their relevance and contribution to the model.

R-square is commonly used in regression analysis to assess how well the variables explain the variation in the response variable, while chi-square is utilized primarily in categorical analysis to indicate the relationship between categorical variables. By leveraging these statistical metrics, the Variable Selection tool helps in identifying which variables should be included in a model based on their statistical significance and influence, enhancing the predictive capability of the model.

This capability of the Variable Selection tool is essential for ensuring that only the most meaningful variables are used, reducing overfitting and improving the interpretability of the model. In contrast, the other tools mentioned serve different purposes: the Model tool focuses on the overall model structure, the Input tool is concerned with how inputs are configured in a modeling context, and the Data tool manages data operations and preparation, rather than directly selecting variables based on statistical criteria.