Learning model trees from evolving data streams
نویسندگان
چکیده
منابع مشابه
Fast Perceptron Decision Tree Learning from Evolving Data Streams
Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffding Trees—Hoeffding Trees with naive Bayes models at the leaf nodes—albeit with increased runtime compared to standard Hoeffding Trees. In this paper, we show that runtime can be reduced by replacing naive Bayes with perceptron c...
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We propose and illustrate a method for developing algorithms that can adaptively learn from data streams that change over time. As an example, we take Hoeffding Tree, an incremental decision tree inducer for data streams, and use as a basis it to build two new methods that can deal with distribution and concept drift: a sliding window-based algorithm, Hoeffding Window Tree, and an adaptive meth...
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ژورنال
عنوان ژورنال: Data Mining and Knowledge Discovery
سال: 2010
ISSN: 1384-5810,1573-756X
DOI: 10.1007/s10618-010-0201-y