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We propose and evaluate alternative ensemble schemes for a new instance based learning classifier, the Randomised Sphere Cover (RSC) classifier. RSC fuses instances into spheres, then bases classification on distance to spheres rather than distance to instances. The randomised nature of RSC makes it ideal for use in ensembles. We propose two ensemble methods tailored to the RSC classifier; αβRSE, an ensemble based on instance resampling and αRSSE, a subspace ensemble. We compare αβRSE and αRSSEarXiv:1409.4936v1 fatcat:gpvx737nhfcwdijs5zp3ouv3tu