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Currently, he is using text mining and classification algorithms to explore the content of central bank communication.
ACM integrates association rule mining and classification.
We applied and tested a range of data mining and classification tools.
Florian Schmedding works at Averbis GmbH and is responsible for customer applications and research projects concerning text mining and classification technologies.
Data mining techniques, including text mining, linguistic feature mining, and classification by text features, can be used to analyze the "caller side" of the transcripts of these calls.
Keramati et al. (2014) not only presented different approaches to data mining and classification methods such as DT, neural networks, SVM, and k-nearest neighbors, but also had the performances of these approaches compared.
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Yet another concern is that data-mining and classification schemes can get things wrong.
Extracting frequent tree patterns which are hidden in data trees is central for analyzing data and is a base step for other data mining processes including association rule mining, clustering and classification.
Deep Learning nonlinear feature extraction can improve data mining results and classification modeling [55].
Based on feature mining and pattern classification, this paper presents a steganalysis technique against reversible data hiding by histogram modification of pixel differences scheme (HMPD).
In data mining and pattern classification, feature extraction and representation methods are a very important step since the extracted features have a direct and significant impact on the classification accuracy.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com