Pages that link to "Item:Q127532"

The following pages link to Greedy function approximation: A gradient boosting machine. (Q127532):

Displaying 50 items.

• Two-level monotonic multistage recommender systems (Q2074300) (← links)
• Interpretable machine learning: fundamental principles and 10 grand challenges (Q2074414) (← links)
• A likelihood-based boosting algorithm for factor analysis models with binary data (Q2076167) (← links)
• Inventory -- forecasting: mind the gap (Q2077906) (← links)
• Screening: from tornado diagrams to effective dimensions (Q2079432) (← links)
• iEnhancer-MFGBDT: Identifying enhancers and their strength by fusing multiple features and gradient boosting decision tree (Q2092240) (← links)
• Predicting S-nitrosylation proteins and sites by fusing multiple features (Q2092265) (← links)
• Adaptive step-length selection in gradient boosting for Gaussian location and scale models (Q2095757) (← links)
• TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions (Q2097447) (← links)
• Optimal policy trees (Q2102338) (← links)
• Wasserstein-based fairness interpretability framework for machine learning models (Q2102385) (← links)
• Machine learning for corporate default risk: multi-period prediction, frailty correlation, loan portfolios, and tail probabilities (Q2103037) (← links)
• A new accelerated proximal boosting machine with convergence rate \(O(1/t^2)\) (Q2103099) (← links)
• A unified neural network framework for extended redundancy analysis (Q2103579) (← links)
• A multi-element non-intrusive polynomial chaos method using agglomerative clustering based on the derivatives to study irregular and discontinuous quantities of interest (Q2106992) (← links)
• Duality gap estimates for a class of greedy optimization algorithms in Banach spaces (Q2117632) (← links)
• InfoGram and admissible machine learning (Q2127228) (← links)
• A review on instance ranking problems in statistical learning (Q2127240) (← links)
• Assessing the value of data for prediction policies: the case of antibiotic prescribing (Q2127308) (← links)
• A hypothesis-free bridging of disease dynamics and non-pharmaceutical policies (Q2127658) (← links)
• Recovering the time-dependent volatility in jump-diffusion models from nonlocal price observations (Q2128477) (← links)
• Mutual information for explainable deep learning of multiscale systems (Q2132642) (← links)
• Inference in Bayesian additive vector autoregressive tree models (Q2135338) (← links)
• Post-model-selection inference in linear regression models: an integrated review (Q2137823) (← links)
• A hierarchical reserving model for reported non-life insurance claims (Q2138622) (← links)
• Modelling and forecasting based on recursive incomplete pseudoinverse matrices (Q2139889) (← links)
• Explainable models of credit losses (Q2140185) (← links)
• A precise high-dimensional asymptotic theory for boosting and minimum-\(\ell_1\)-norm interpolated classifiers (Q2148995) (← links)
• The added value of dynamically updating motor insurance prices with telematics collected driving behavior data (Q2155841) (← links)
• Uniform approximation rates and metric entropy of shallow neural networks (Q2157931) (← links)
• Variational inference with NoFAS: normalizing flow with adaptive surrogate for computationally expensive models (Q2162034) (← links)
• One-stage tree: end-to-end tree builder and pruner (Q2163237) (← links)
• Techniques to improve ecological interpretability of black-box machine learning models. Case study on biological health of streams in the United States with gradient boosted trees (Q2163504) (← links)
• Nonconvex regularization for sparse neural networks (Q2168678) (← links)
• Global sensitivity analysis in epidemiological modeling (Q2171531) (← links)
• Actuarial intelligence in auto insurance: claim frequency modeling with driving behavior features and improved boosted trees (Q2172034) (← links)
• Interpreting deep learning models with marginal attribution by conditioning on quantiles (Q2172619) (← links)
• Grouped feature importance and combined features effect plot (Q2172623) (← links)
• Conclusive local interpretation rules for random forests (Q2172632) (← links)
• Banzhaf random forests: cooperative game theory based random forests with consistency (Q2182870) (← links)
• Optimizing predictive precision in imbalanced datasets for actionable revenue change prediction (Q2184072) (← links)
• Optimal nonlinear signal approximations based on piecewise constant functions (Q2192284) (← links)
• Transfer learning by mapping and revising boosted relational dependency networks (Q2203326) (← links)
• Random forest with acceptance-rejection trees (Q2203396) (← links)
• \textsc{Treant}: training evasion-aware decision trees (Q2212514) (← links)
• Interpretable regularized class association rules algorithm for classification in a categorical data space (Q2212562) (← links)
• Double-slicing assisted sufficient dimension reduction for high-dimensional censored data (Q2215728) (← links)
• Fast greedy \(\mathcal{C} \)-bound minimization with guarantees (Q2217455) (← links)
• Invariance, causality and robustness (Q2218071) (← links)
• A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates (Q2218385) (← links)