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In this research we present a new framework and associated algorithms for mining high speed data streams that take advantage of concept recurrence. Different from previous work our approach detects volatility in a stream and then matches the learning paradigm to the degree of volatility. In high volatility stream segments a decision forest is used as the learning mechanism whereas in low volatility...
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