The output mixes the outputs of the PLS regression with classical discriminant analysis outputs such as confusion matrix. PLS discriminant analysis offers an interesting alternative to classical linear discriminant analysis. An observation is associated to the category that has an equation with the highest value. Finally, as PLS regression, it is adapted when multicollinearity between explanatory variables is high.Īs many models as categories of the dependent variable are obtained. When there are missing values, PLS discriminant analysis can be applied on the data that is available. For example, when the number of observations is low and when the number of explanatory variables is high. PLS discriminant analysis can be applied in many cases when classical discriminant analysis cannot be applied. XLSTAT uses the PLS2 algorithm applied on the full disjunctive table obtained from the qualitative dependent variable. The PLS discriminant analysis uses the PLS algorithm to explain and predict the membership of observations to several classes using quantitative or qualitative explanatory variables. The size of the training set is defined by a row number percentage from the initial data set.PLS regression can be adapted to fit discriminant analysis (PLS-DA). The rows of each set are randomly drawn from the initial dataset. ![]() Training and test sets (%): Data are split into two parts – a training set and a test set.The size of the training set is defined by a number of rows. Training and test sets: Data are split into two parts – a training set and a test set.User defined: A variable indicates the frequency of each observation within the output sample.In each stratum, the number of sampled observations is proportional to a relative frequency supplied by the user. ![]() Random stratified (3 ): Rows are chosen at random within N strata defined by the user.In each stratum, the number of sampled observations is proportional to the relative frequency of the stratum. Random stratified (2): Rows are chosen at random within N strata defined by the user. ![]()
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