Scalable real-time classification of data streams with concept drift
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چکیده
منابع مشابه
Scalable real-time classification of data streams with concept drift
Inducing adaptive predictive models in real-time from high throughput data streams is one of the most challenging areas of Big Data Analytics. The fact that data streams may contain concept drifts (changes of the pattern encoded in the stream over time) and are unbounded, imposes unique challenges in comparison with predictive data mining from batch data. Several real-time predictive data strea...
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SUMMARY Increasing access to large, nonstationary datasets and corresponding demands to analyze these data has led to the development of new online algorithms for performing machine learning on data streams. An important feature of many real-world data streams is " concept drii, " whereby the characteristics of the data can change arbitrarily over time. e presence of concept drii in a data stre...
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Increasing access to incredibly large, nonstationary datasets and corresponding demands to analyse these data has led to the development of new online algorithms for performing machine learning on data streams. An important feature of real-world data streams is " concept drift, " whereby the distributions underlying the data can change arbitrarily over time. The presence of concept drift in a d...
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ژورنال
عنوان ژورنال: Future Generation Computer Systems
سال: 2017
ISSN: 0167-739X
DOI: 10.1016/j.future.2017.03.026