Scalable Data Quality for Big Data: The Pythia Framework for Handling Missing Values
نویسندگان
چکیده
منابع مشابه
Scalable Data Quality for Big Data: The Pythia Framework for Handling Missing Values.
Solving the missing-value (MV) problem with small estimation errors in large-scale data environments is a notoriously resource-demanding task. The most widely used MV imputation approaches are computationally expensive because they explicitly depend on the volume and the dimension of the data. Moreover, as datasets and their user community continuously grow, the problem can only be exacerbated....
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ژورنال
عنوان ژورنال: Big Data
سال: 2015
ISSN: 2167-6461,2167-647X
DOI: 10.1089/big.2015.0002