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This method is unique in that it directly encodes reading experience of radiologists without resorting to a statistical classifier to implicitly extract classification rules from labeled data.
In this paper, we experiment with four rule-based algorithms [ 51] that extract classification models in the form of logic formulas and we compare them with other state-of-the-art classifiers, such as Support Vector Machines [ 58, 69] and Nearest Neighbor [ 70].
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The extracted classification rules are in the form of IF THEN rules which can be easily understood by human.
In total, we extracted classification and labelling data for 4136 substances (of which 139 were mixtures) from Annex VI of the CLP Regulation.
Furthermore, high-risk subgroups were identified from extracted classification rules with a support of more than 100 instances.
Similarly, reverse correlation methods can be used to extract a classification image in a task that essentially requires familiarity judgments [ 7, 25], but such a classification image only provides information about the mean or mode of the prior [ 26] and thus remains uninformative about the rich structural details of the priors we have demonstrated.
In this paper we focus on the continuous wavelet transform (CWT) to extract the classification features.
This work includes three important parts: Feature Extracting, Classification, and Decision Fusion.
To learn more about these drugs, we extracted their classification information from the Anatomical Therapeutic Chemical (ATC) classification from KEGG (Kyoto Encyclopedia of Genes and Genomes) (20).
Extracting comprehensible classification rules is the most emphasized concept in data mining researches.
The HOG features of 1,764 in a verified ROI were extracted for classification.
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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