Adaptive Online Prediction Using Weighted Windows
نویسندگان
چکیده
We propose online prediction algorithms for data streams whose characteristics might change over time. Our algorithms are applications of online learning with experts. In particular, our algorithms combine base predictors over sliding windows with different length as experts. As a result, our algorithms are guaranteed to be competitive with the base predictor with the best fixed-length sliding window in hindsight. key words: machine learning, data stream, online learning, sliding window
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ورودعنوان ژورنال:
- IEICE Transactions
دوره 94-D شماره
صفحات -
تاریخ انتشار 2011