Wavelength selection is a fundamental and critical step in near infrared spectral analysis, which can improve the prediction performance and enhance the interpretability of the model. Motivated by the appealing properties of the distance correlation, a novel wavelength interval selection algorithm, named iterative distance correlation combined with PLS regression (IDC-PLS), is developed. To obtain all the possible wavelength intervals, our method mainly consists of two steps. First, an effective iterative procedure based on distance correlation is used to screen wavelength interval variables. ...
