The origins of chemometrics within chemical pattern recognition of the 1960s and 1970s are described. Trends
subsequent to that era have reduced the input of pattern recognition within mainstream chemometrics, with a
few approaches such as PLS-DA and SIMCA becoming dominant. Meanwhile vibrant and ever expanding
literature has developed within machine learning and applied statistics which has hardly touched the chemometric
community. Within the wider scientific community, chemometric originated pattern recognition
techniques such as PLS-DA have been widely adopted largely due to the existence of widespread packages, but
are widely misunderstood and sometimes misapplied.