On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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10 results for “TreeSHAP”

Fast TreeSHAP: Accelerating SHAP Value Computation for Treescs.LG

Two new algorithms speed up TreeSHAP computation for tree-based models.

problem Slow computation of SHAP values on tree-based models.

method Two new algorithms, Fast TreeSHAP v1 and v2, designed to improve computational efficiency.

result Fast TreeSHAP v2 is 2.5x faster than TreeSHAP, with slightly higher memory usage.

TreeSHAP SHAP values machine learning interpretation exponential time

2021-09-20abs ↗pdf ↗

Enhancing User' s Income Estimation with Super-App Alternative Datacs.LG

Paper uses Super-App data to improve income estimation models.

problem Improving accuracy of income estimation models.

method TreeSHAP method for Stochastic Gradient Boosting Interpretation.

result Alternative data from Super-Apps capture more information than traditional financial data.

income estimation Super-Apps alternative data TreeSHAP behavioral patterns

2021-04-12abs ↗pdf ↗

Super-App Behavioral Patterns in Credit Risk Models: Financial, Statistical and Regulatory Implicationsq-fin.GN

Alternative app data improves credit scoring for underserved borrowers.

problem Improving credit scoring for low-wealth and young individuals.

method Use of alternative data from app-based marketplaces, validated with TreeSHAP method.

result Alternative data sources predict financial behavior better than traditional bureau data.

credit scoring alternative data app-based marketplaces TreeSHAP underbanked

2020-05-09abs ↗pdf ↗

Approximating Score-based Explanation Techniques Using Conformal Regressioncs.LG

Proposes approximating computationally expensive explainability techniques using conformal regression.

problem Computational expense of score-based explainability techniques limits their applicability in time-critical contexts.

method Uses conformal prediction framework to approximate SHAP and TreeSHAP explanations.

result Significantly improves execution time and produces tight validity guarantees.

explainable AI conformal prediction SHAP TreeSHAP approximation

2023-08-23abs ↗pdf ↗

Tree Ensemble Explainability through the Hoeffding Functional Decomposition and TreeHFD Algorithmstat.ML

TreeHFD algorithm explains tree ensemble models through hierarchical orthogonality.

problem Difficulty in explaining black-box tree ensemble models.

method TreeHFD algorithm using hierarchical orthogonality constraints.

result TreeHFD estimates Hoeffding decomposition from data samples.

Tree Ensemble Explainability Hoeffding Decomposition TreeSHAP Hierarchical Orthogonality

2025-10-28abs ↗pdf ↗

Fast Estimation of Partial Dependence Functions using Treescs.LG

A new tree-based estimator, FastPD, efficiently estimates PD functions for machine learning models.

problem Efficiently estimating Partial Dependence functions for machine learning models.

method Proposes a new tree-based estimator, FastPD, to estimate PD functions.

result FastPD consistently estimates the desired population quantity and improves complexity from quadratic to linear.

Partial Dependence Machine Learning Tree-Based Estimator Efficiency Consistency

2024-10-17abs ↗pdf ↗

Proxy-Based Approximation of Shapley and Banzhaf Interactionscs.LG

ProxySHAP approximates Shapley and Banzhaf interactions efficiently.

problem Efficient estimation of complex machine learning interactions.

method ProxySHAP combines tree-based proxy models with residual correction.

result ProxySHAP achieves state-of-the-art interaction approximation quality.

machine learning interaction analysis proxy models residual correction Shapley

2026-05-21abs ↗pdf ↗

Individualized and Global Feature Attributions for Gradient Boosted Trees in the Presence of

\ell_2

Regularizationstat.ML

Proposes new attribution methods for trees with regularization.

problem Feature attribution for trees trained with regularization.

method Prediction Decomposition Attribution (PreDecomp) and TreeInner.

result TreeInner shows state-of-the-art feature selection performance.

Gradient Boosted Trees Feature Attribution Regularization Total Gain Debiased Global Attribution

2022-11-08abs ↗pdf ↗

STRIDE: Subset-Free Functional Decomposition for XAI in Tabular Settingscs.LG

STRIDE improves explainable AI by efficiently decomposing feature interactions without subset enumeration.

problem Lack of expressive power and high computational cost in existing XAI frameworks.

method STRIDE uses a functional decomposition approach in RKHS, avoiding subset enumeration and focusing on orthogonal components.

result STRIDE achieves a 3.0 times speedup over TreeSHAP and a high R^2 of 0.93 for feature reconstruction.

explainable AI feature interactions kernel methods functional decomposition tabular data

2025-09-11abs ↗pdf ↗

Local MDI+: Local Feature Importances for Tree-Based Modelscs.LG

Local MDI+ improves feature importance for tree-based models, enhancing interpretability and performance.

problem Lack of instance-specific feature importance for tree-based models.

method Local MDI+ extends MDI+ framework to provide instance-specific feature importances.

result Local MDI+ outperforms existing baselines, improving predictive performance by 10%.

feature importance tree-based models local interpretability random forests gradient boosting

2025-06-10abs ↗pdf ↗