Your English writing platform
Discover LudwigExact(59)
Linear support vector machine.
linear support mappings for convex resp.
For final classification, we utilize the linear support vector classifier [28].
Linear support vector machines were implemented whenever the examples turned out to be linearly separable.
The latter is used as input to a linear support vector machine classifier.
Features extracted using KPCA are classified using linear support vector machines.
Linear support vector machines showed to have a convincing performance on large-scale data sets.
With the resulting codebook, we train a linear support vector machine (lSVM).
A linear support vector machine (SVM) is considered, along with several nonlinear classifiers.
Support vector machines are basically divided into two groups as linear support vector machines and nonlinear support vector machines.
Decision tree (DT) and linear support vector machines (SVM) and probabilistic neural network (PNN) algorithms were used as classifiers.
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