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Spatial data mining is defined as the automatic process of discovering interesting and implicit knowledge from large amounts of spatial data.
Sentiment analysis, which is also referred to as opinion mining, is defined as the task of finding opinions of authors about specific entities [58].
Data mining is defined as a non-trivial process of identifying valid, novel, potentially useful and ultimately understandable patterns in data [1].
Text mining is defined as the process of retrieving or extracting small nuggets of relevant information from large collections of textual data [ 4].
Data mining is defined as part of knowledge discovery in databases and draws on the fields of statistics, machine learning, pattern recognition, and database management and can be able to extract interesting and useful material from these large datasets.
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For this study, the medium-size mine is defined with a production rate of 7.6 million bank m3 of overburden to be excavated annually.
Briefly, areas to be mined are defined and the vegetation cleared.
The width of the backfilling wall also influences the stability and cost of the whole system for retaining the entryway where the mining height is defined.
The emerging substrings mining problem is defined as follows.
In pattern recognition and data mining, recall is defined as the fraction of relevantly retrieved instances.
Predictive data mining task is defined by the target attribute [ 24].
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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