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The lasso catch him around the neck; he is obliged to remain.
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But the lasso slipped from the horns and the goat ran away.
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He threw the lasso, drew it tight and the goat was captured.
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One was found in a lasso, with which the natives catch them.
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Then I can lasso the rooster and make an ostrich of him.
Использование термина least absolute shrinkage and selection operator на английском
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The leastabsoluteshrinkageandselectionoperator regression analysis was used for feature selection.
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The leastabsoluteshrinkageandselectionoperator penalized Cox regression was adopted to construct a radiomic signature.
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A radiomic signature was constructed using the leastabsoluteshrinkageandselectionoperator algorithm in the training set.
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The final model was created using a penalized regression method known as the leastabsoluteshrinkageandselectionoperator.
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The leastabsoluteshrinkageandselectionoperator regression were applied to optimize factor selection for the poor recovery risk model.
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Multinomial leastabsoluteshrinkageandselectionoperator analysis identified 269 genetic variants that showed different frequencies among the three ethnic groups.
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Then, we generated a 16-mRNA signature score system through leastabsoluteshrinkageandselectionoperator (LASSO) Cox regression analysis.
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Furthermore, a leastabsoluteshrinkageandselectionoperator (LASSO) regression analysis was performed to generate TME-related immune prognostic signatures.
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The radiomics features were selected with the leastabsoluteshrinkageandselectionoperator algorithm, and prediction models were constructed with multiple classifiers.
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A multivariable leastabsoluteshrinkageandselectionoperator regression analysis was used to adjust for patient pre- and intraoperative risk factors for mortality.
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For these genes, leastabsoluteshrinkageandselectionoperator (lasso) regression model was applied and validated to build a diagnostic risk score model.
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Multiple regression analysis was performed using generalized linear models (GLMs) and the leastabsoluteshrinkageandselectionoperator (LASSO) approach for variable selection.
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The statistical method of LASSO ( leastabsoluteshrinkageandselectionoperator) was used to select important placental measures that would have better predictability for outcomes.
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A novel preconditioned leastabsoluteshrinkageandselectionoperator method yielded an average r s of 0.38 on 100 bootstrapped data sets.
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A logistic leastabsoluteshrinkageandselectionoperator (LASSO) regression with 10-fold cross-validation was used to select potential predictors among 47 candidate variables.
Translations for least absolute shrinkage and selection operator