Data streams are produced continuously at a high speed. Most data stream mining techniques address this challenge by using adaptation and approximation techniques. Adapting to available resources has been addressed recently. Although these techniques ensure the continuity of the data mining process under resource limitation, the quality of the output is still an open issue. In this paper, we propose a generic model that guarantees the quality of the output while maintaining efficient resource consumption. The model works on estimating the quality of the output given the available resources. Only a subset of these resources will be used that guarantees the minimum quality loss. The model is generalized for any data stream mining technique.