Cover Image

Training Gradient Boosted Decision Trees on Tabular Data Containing Label Noise for Classification Tasks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Eisenbürger, Anita, Otten, Daniel, Hudde, Anselm, Hopfgartner, Frank
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Backdoor attacks on DNN and GBDT -- A Case Study from the insurance domain
by: Kühlem, Robin, et al.
Published: (2024)

Gradient Boosting Decision Trees on Medical Diagnosis over Tabular Data
by: Yıldız, A. Yarkın, et al.
Published: (2024)

Improving Data Quality with Training Dynamics of Gradient Boosting Decision Trees
by: Ponti, Moacir Antonelli, et al.
Published: (2022)

Challenging Gradient Boosted Decision Trees with Tabular Transformers for Fraud Detection at Booking.com
by: Krutikov, Sergei, et al.
Published: (2024)

GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data
by: Marton, Sascha, et al.
Published: (2023)

Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
by: Jolicoeur-Martineau, Alexia, et al.
Published: (2023)

Robust-GBDT: GBDT with Nonconvex Loss for Tabular Classification in the Presence of Label Noise and Class Imbalance
by: Luo, Jiaqi, et al.
Published: (2023)

LLM Meeting Decision Trees on Tabular Data
by: Ye, Hangting, et al.
Published: (2025)

Robust-Multi-Task Gradient Boosting
by: Emami, Seyedsaman, et al.
Published: (2025)

Transformers Boost the Performance of Decision Trees on Tabular Data across Sample Sizes
by: Jayawardhana, Mayuka, et al.
Published: (2025)

Gradient Boosting Trees and Large Language Models for Tabular Data Few-Shot Learning
by: Huertas, Carlos
Published: (2024)

Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise
by: Khanal, Bidur, et al.
Published: (2024)

Gradient Boosting Decision Tree with LSTM for Investment Prediction
by: Yu, Chang, et al.
Published: (2025)

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification
by: Shi, Ruxue, et al.
Published: (2025)

Gradient-Weight Alignment as a Train-Time Proxy for Generalization in Classification Tasks
by: Hölzl, Florian A., et al.
Published: (2025)

Regretful Decisions under Label Noise
by: Nagaraj, Sujay, et al.
Published: (2025)

Talking Trees: Reasoning-Assisted Induction of Decision Trees for Tabular Data
by: Yakushev, George, et al.
Published: (2025)

NCART: Neural Classification and Regression Tree for Tabular Data
by: Luo, Jiaqi, et al.
Published: (2023)

BoostLLM: Boosting-inspired LLM Fine-tuning for Few-shot Tabular Classification
by: Wang, Yi-Siang, et al.
Published: (2026)

UTBoost: Gradient Boosted Decision Trees for Uplift Modeling
by: Gao, Junjie, et al.
Published: (2023)

Better by Default: Strong Pre-Tuned MLPs and Boosted Trees on Tabular Data
by: Holzmüller, David, et al.
Published: (2024)

HyperFast: Instant Classification for Tabular Data
by: Bonet, David, et al.
Published: (2024)

Robust Loss Functions for Training Decision Trees with Noisy Labels
by: Wilton, Jonathan, et al.
Published: (2023)

When Do Neural Nets Outperform Boosted Trees on Tabular Data?
by: McElfresh, Duncan, et al.
Published: (2023)

Exploring Loss Design Techniques For Decision Tree Robustness To Label Noise
by: Sztukiewicz, Lukasz, et al.
Published: (2024)

Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data
by: Lin, Huawei, et al.
Published: (2025)

SecureBoost+: Large Scale and High-Performance Vertical Federated Gradient Boosting Decision Tree
by: Fan, Tao, et al.
Published: (2021)

A Versatile Variational Quantum Kernel Framework for Non-Trivial Classification
by: Yuhan, Jiang, et al.
Published: (2025)

Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise
by: Shubham, Kumar, et al.
Published: (2026)

FACROC: a fairness measure for FAir Clustering through ROC curves
by: Quy, Tai Le, et al.
Published: (2025)

Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning
by: Nam, Jaehyun, et al.
Published: (2024)

Unmasking Trees for Tabular Data
by: McCarter, Calvin
Published: (2024)

Learning to Retrieve with Weakened Labels: Robust Training under Label Noise
by: Sharma, Arnab
Published: (2025)

Mitigating Label Noise through Data Ambiguation
by: Lienen, Julian, et al.
Published: (2023)

Unsupervised Anomaly Detection for Tabular Data Using Noise Evaluation
by: Dai, Wei, et al.
Published: (2024)

FairFinGAN: Fairness-aware Synthetic Financial Data Generation
by: Quy, Tai Le, et al.
Published: (2026)

DeGLIF for Label Noise Robust Node Classification using GNNs
by: Kumar, Pintu, et al.
Published: (2025)

TABFAIRGDT: A Fast Fair Tabular Data Generator using Autoregressive Decision Trees
by: Panagiotou, Emmanouil, et al.
Published: (2025)

On the Convergence of Multicalibration Gradient Boosting
by: Haimovich, Daniel, et al.
Published: (2026)

An Automatic Prompt Generation System for Tabular Data Tasks
by: Akella, Ashlesha, et al.
Published: (2024)