Canonical Correlation Analysis Data Envelopment Analysis Efficiency Variable Aggregation Multivariate Statistics Data Mining
Institute of Information Theories and Applications FOI ITHEA
In the nonparametric framework of Data Envelopment Analysis the statistical properties of its
estimators have been investigated and only asymptotic results are available. For DEA estimators results of
practical use have been proved only for the case of one input and one output. However, in the real world
problems the production process is usually well described by many variables. In this paper a machine learning
approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied
for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago.