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For example, in the dataset of 30 yeast genes, 89.2% of the activations have R2 scores < 3, and 91.4% of the inhibitions have R2 scores > 6.
Each binary pattern (string or example) in the dataset can also be interpreted as a digital logic rule stating the correct output for a given set of values of the input variables.
Each example in the dataset has an observed label (positive or negative in the case of binary classification) that represents its actual class, and a predicted label (again, either positive or negative) that is predicted by the classifier.
To estimate the origin of the infection in those for whom transmission from identified, PSCs was not confirmed, cases were classified as likely to be due to reactivation if the strain was the first or only example in the dataset and as recent infection if the strain was part of an existing cluster.
For example, in the dataset of nurses and midwives with a registration, 23.09% (N = 4018) did not report birth dates, 96.78% (N = 16 845) did not report marital status, 38.21% (N = 6651) did not report information about home district, and 28.96% (N = 5040) did not report information about birth district.
For example, in the dataset eg-DHS_41-ch.dta (survey of Egypt 2000) there were three groups of variables pointing at the date when DTP3 was received (three variables for the day, three for the month and three for the year), all sharing the same key terms.
Similar(54)
For example, in case the dataset is split horizontally, we could retrieve them all in the central repository data warehouse using selection operator.
We intent to filter out unlikely examples in the dataset to obtain a clear dissimilarity matrix.
This measure returns the ratio of the number of examples in the dataset to the number of attributes.
For this purpose, it builds a minimum spanning tree over the entire dataset and returns the ratio of the number nodes of the spanning tree that are connected and belong to different classes to the total number of examples in the dataset.
The examples in the dataset were randomly split into three sets.
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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