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The main disadvantage of machine learning models is their reliance on labelled data.
Section 2 introduces a graph data model based on (labelled) property graphs.
Two different lithotypes were used for the tests: Globigerina Limestone and Giallo Terra di Siena, from now on labelled as GL and GS, respectively, differing for porosity and mineralogical composition.
Clearly, classification accuracy must be assessed on labelled samples 'unseen' during training.
To support model checking for composition and verification of Web services against a pre-defined goal in an effective manner, our work suggested representing a repository of Web services as a mathematical model, based on Labelled Transition System (LTS), known as LTS for Web Services (LTS4WS).
In the supervised approach a classification model is typically trained based on labelled training documents.
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They may appear on labels as "seasoning".
This is primarily because most approaches rely on labeled data.
Most supervised feature selection methods are dependent on labeled data.
We prefer to concentrate on labeling weaknesses.
President Obama campaigned on labeling GMOs back in 2007.
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