Your English writing platform
Discover LudwigSuggestions(2)
Exact(17)
To account for this variability, we classified the data set of pneumatic controllers emissions into the main controller applications: separator, process heater, compressor, dehydrator, wellhead and plunger lift.
The dendrogram classified the data into three cluster membership.
We also classified the data produced by the remaining 21 subjects in the DEAP dataset.
The PCA classified the data into 3 major groups, namely non-transgenic, transgenic and dysplasia (Figure 3).
For the risk of NVAF associated with Hcy levels, we classified the data into quartiles based on the distribution of this parameter among patients and controls (Q1:≤9.7; Q2:9.8–12.1; Q3:12.2–16.0; Q4:≥16.1 µmol/L).
The resulting DF1 classified the data into young and old.
Similar(43)
Finally, we use a Random Forest (RF) classifier to classify the data according to the Association for the Advancement of Medical Instrumentation AAMII) standards (1988).
The goal of SVM is to construct a classifier that classifies the data instances in the testing data.
Most decision tree classifiers are designed to classify the data with categorical or Boolean class labels.
Study shows a library of features, and classifiers are available to classify the data.
These examples provide particular situations where low-level classifiers by themselves have trouble to correctly classify the data items in the test set.
Write better and faster with AI suggestions while staying true to your unique style.
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