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cs.LG2018
Impact of Biases in Big Data
Patrick Glauner, Petko Valtchev, Radu State
The underlying paradigm of big data-driven machine learning reflects the desire of deriving better conclusions from simply analyzing more data, without the necessity of looking at…
cs.LG2018
On the Reduction of Biases in Big Data Sets for the Detection of Irregular Power Usage
Patrick Glauner, Radu State, Petko Valtchev +1
In machine learning, a bias occurs whenever training sets are not representative for the test data, which results in unreliable models. The most common biases in data are arguably…