Model selection is a critical step in data analysis and machine learning, particularly in prediction tasks where the true underlying model is rarely known. Although numerous techniques have been ...

Predictor variables in statistical models can be treated as either continuous or categorical. Usually, this is a very straightforward decision. Categorical predictors, like treatment group, marital ...

Forecasting models predict the future values of a series using two sources of information: the past values of the series and the values of other time series variables. Other variables used to predict ...

Decision trees are a simple but powerful prediction method. Figure 1: A classification decision tree is built by partitioning the predictor variable to reduce class mixing at each split. The ...

Despite having a similar post-operative complication profile, cardiac valve operations are associated with a higher mortality rate compared to coronary artery bypass grafting (CABG) operations. For ...

It is my understanding that large imbalances in predictor variable categories (e.g., a sample with 10% males and 90% females) will reduce a variable's importance (variable importance measure) and ...