Pages that link to "Item:Q722722"
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The following pages link to On the choice and influence of the number of boosting steps for high-dimensional linear Cox-models (Q722722):
Displaying 9 items.
- Boosting in Cox regression: a comparison between the likelihood-based and the model-based approaches with focus on the R-packages \textit{CoxBoost} and \textit{mboost} (Q736636) (← links)
- Two-step sparse boosting for high-dimensional longitudinal data with varying coefficients (Q1615281) (← links)
- Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation (Q1722724) (← links)
- A likelihood-based boosting algorithm for factor analysis models with binary data (Q2076167) (← links)
- Interaction forests: identifying and exploiting interpretable quantitative and qualitative interaction effects (Q2129608) (← links)
- Can matching improve the performance of boosting for identifying important genes in observational studies? (Q2255762) (← links)
- EEBoost: A General Method for Prediction and Variable Selection Based on Estimating Equations (Q5256421) (← links)
- A boosting first-hitting-time model for survival analysis in high-dimensional settings (Q6103255) (← links)
- Stability of clinical prediction models developed using statistical or machine learning methods (Q6595097) (← links)
