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This paper describes a portable, machine learning-based approach to Java optimisation. This approach uses an instancebased learning scheme to select good transformations drawn from Pugh's Unified Transformation Framework [11]. This approach was implemented and applied to a number of numerical Java benchmarks on two platforms. Using this scheme, we are able to gain over 70% of the performance improvement found when using an exhaustive iterative search of the best compiler optimisations. Thus we have a scheme that gives a high level of portable performance without any excessive compilations.