1. A method for classifying unknown fabric samples, comprising: providing an unknown fabric sample; collecting spectral data of the unknown fabric sample using a near-infrared reflection spectrometer to give a spectrum of an unknown sample; collecting near-infrared spectral data of a plurality of fabric samples to create a spectral database for regression analysis, wherein the fabric samples are of known fabric types; performing a principal component analysis and a regression of the spectral data for each of the fabric samples of each known fabric type; and using soft independent modeling of class analogy (“SIMCA”) to compare the spectrum of the unknown sample to similar spectral data of the known standard representing the known fabric type to classify the unknown fabric sample into either one or more of the known fabric types.