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We next built a linear classifier model by multivariate Cox regression to predict prognostic outcomes of HCC patients after curative surgery This analysis detected a considerable fraction of variance in HCC prognosis and the area under the ROC curve was about 70%.
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To make a fair comparison with the proposed multiple criteria method in this study, only the top 39 genes were chosen to build a linear classifier to be applied to database 2 15 as in the previous section.
Embedded feature selection techniques are those in which the feature selection is intrinsic to the classifier, such as employing l1 regularization on a linear classifier, resulting in a model built using only a small number of features (those with non-zero weights).
Finally, a linear classifier is designed.
For instance, a nonlinear learning method like kNN will in some cases produce a linear classifier.
And you can either learn a linear classifier, or you can learn something more complicated that's non-linear.
Two fuzzy classifiers, a Bayesian classifier and a linear classifier, are designed for vocal folds damage detection based on human vowel voices /a:/ and /i:/ only, and the fuzzy classifiers are compared against the Bayesian classifier and linear classifier.
After feature extraction, we apply a linear classifier for classification.
The original SVM classifier was a linear classifier.
These features were fed into a linear classifier.
Firstly it is a linear classifier and cannot allow for non linear relationships in the data.
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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