Quantitative Structure–Activity Relationship (QSAR) modeling of juvenile hormone activity: Comparison of validation procedures

Four regression methods are used to fit QSAR models for a large set of juvenile hormone mimetic compounds, using a diverse set of descriptors. The proper application of cross-validation is summarized and applied to both the model selection and verification steps, with comparison to the use of a holdout sample. Implementation of the evaluation of a modelʹs predictive ability at the correct point in the procedure is emphasized. A recent regression methodology, the elastic net, is shown to produce a reduced set of predictors while retaining predictive ability.