FEATURE-SELECTION FOR THE DISCRIMINATION BETWEEN POLLUTION TYPES WITHPARTIAL LEAST-SQUARES MODELING

Discrimination between different types of pollution was carried out wi th partial least squares (PLS), The data sets concern steelworks and g alvanization sludges and urban sludges coming from two different depur ation steps, A method of feature selection based on the closed form of the PLS model is proposed and satisfactory-classification rates were achieved(correct classification rate values between 94 and 70%), The r esults show that feature selection can improve the performance of the PLS classification and reduce the number of analytical determinations to be performed. Outlying samples were detected and omitted before the classification.