Your English writing platform
Discover LudwigExact(2)
Most of the existing approaches perform data classification based on a distance measure in a multivariate feature space.
SVM is a statistical discrimination procedure that finds a linear separation surface in the high-dimensional multivariate feature space that maximally separates the training data into two classes as specified by the pre-assigned labels (in this case, high and low severity groups).
Similar(58)
Pairwise scatter plots of the first five principal components of the feature space (multivariate phenotypes) of the single-dsRNA effects against all target genes are shown.
Thus the Gaussian mixture model can be estimated in the feature space with each component satisfying multivariate Gaussianity.
Among the hub genes selected, some may be irrelevant to the trait of interest; therefore, we performed multivariate logistic regression modeling to reduce the dimensionality of the feature space and to identify the best subset of hub genes (those that have the strongest correlations with the phenotype in question).
Based on T2 and SPE charts in the feature space, KPCA was applied to fault detection in two example systems: a simple multivariate process and the simulation benchmark of the biological wastewater treatment process.
Feature space.
Feature space dimensionality reduction.
(e) Feature space.
High-dimensional feature space.
(a) Evaluation (LDA feature space) (b) Test (LDA feature space).
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