Quantitative structure-retention relationship for the Kovats retention indices of a large set of terpenes: a combined data splitting-feature selection strategy.

A data set consisting of a large number of terpenoids, the widely distributed compounds in nature that are found in abundance in higher plants, have been used to develop a quantitative structure property relationship (QSPR) for their Kovats retention index. QSPR models are usually obtained by splitting the data into two sets including calibration (or training) and prediction (or validation). All model building steps, especially feature selection procedure, are performed using this initial splitting, and therefore the performances of the resulted models are highly dependent on the initial data splitting.