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Discover Ludwig"data description" is a common phrase used in written English and can be used in almost any context where you are discussing data or statistics.
For example: "This report contains a detailed data description of our sales for the past year."
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"Data description" section describes the Baidu Index and capital data.
Daux, V. et al. An open-access database of grape harvest dates for climate research: data description and quality assessment.
The SVDD monitoring scheme manifests clear benefits over other one-class classification methods, i.e., principal component analysis (PCA) data description and nearest-neighbor data description.
Furthermore, the data description is provided including behavioral data as well as EEG data.
The support vector data description (SVDD) classifier achieved 100% calibration accuracy.
The external EM fields are modeled accurate to the input data description.
Data description language (DDL) is used to define the structure of the data.
Then, the incremental rough support vector data description (IRSVDD) is designed based on the RSVDD.
Support Vector Data Description (SVDD) is a support vector based learning algorithm for anomaly detection.
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The key iTools functionalities are storage, searching, traversal and retrieval of resources and their corresponding meta-data description.
The accuracy of data description is better than ca. 4%.
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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