:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Chwilczyński, Sebastian, Brzezinski, Dariusz
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2502.19122
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ART: Actually Robust Training
by: Chwilczyński, Sebastian, et al.
Published: (2024)

Weighted Isolation and Random Cut Forest Algorithms for Anomaly Detection
by: Yeom, Sijin, et al.
Published: (2022)

Signature Isolation Forest
by: Campi, Marta, et al.
Published: (2024)

Online Isolation Forest
by: Leveni, Filippo, et al.
Published: (2025)

Robust Isolation Forest using Soft Sparse Random Projection and Valley Emphasis Method
by: Kang, Hun, et al.
Published: (2025)

Extended Isolation Forest with feature sensitivities
by: Donhauzer, Illia
Published: (2026)

Detecting Anomalies Using Rotated Isolation Forest
by: Monemizadeh, Vahideh, et al.
Published: (2025)

Theoretical Investigation on Inductive Bias of Isolation Forest
by: Zheng, Qin-Cheng, et al.
Published: (2025)

Random Forest Calibration
by: Shaker, Mohammad Hossein, et al.
Published: (2025)

Heterogeneous Random Forest
by: Kim, Ye-eun, et al.
Published: (2024)

Isolation Forest in Novelty Detection Scenario
by: Ulrich, Adam, et al.
Published: (2025)

Predicted-occupancy grids for vehicle safety applications based on autoencoders and the Random Forest algorithm
by: Nadarajan, Parthasarathy, et al.
Published: (2025)

Enhancing Interpretability and Generalizability in Extended Isolation Forests
by: Arcudi, Alessio, et al.
Published: (2023)

siForest: Detecting Network Anomalies with Set-Structured Isolation Forest
by: Djidjev, Christie
Published: (2024)

Jacobian Aligned Random Forests
by: Rauniyar, Sarwesh
Published: (2025)

Improving Random Forests by Smoothing
by: Liu, Ziyi, et al.
Published: (2025)

Neural Random Forest Imitation
by: Reinders, Christoph, et al.
Published: (2019)

Lassoed Forests: Random Forests with Adaptive Lasso Post-selection
by: Shang, Jing, et al.
Published: (2025)

Exogenous Randomness Empowering Random Forests
by: Mei, Tianxing, et al.
Published: (2024)

Autoencoding Random Forests
by: Vu, Binh Duc, et al.
Published: (2025)

Hyperbolic Random Forests
by: Doorenbos, Lars, et al.
Published: (2023)

Forest-Guided Clustering -- Shedding Light into the Random Forest Black Box
by: Sousa, Lisa Barros de Andrade e, et al.
Published: (2025)

When do Random Forests work?
by: Revelas, C., et al.
Published: (2025)

Grafting: Making Random Forests Consistent
by: Waltz, Nicholas
Published: (2024)

Prediction Error Estimation in Random Forests
by: Krupkin, Ian, et al.
Published: (2023)

Random Forest-Supervised Manifold Alignment
by: Rhodes, Jake S., et al.
Published: (2024)

Open Set Recognition for Random Forest
by: Feng, Guanchao, et al.
Published: (2024)

Random Forest Weighted Local Fréchet Regression with Random Objects
by: Qiu, Rui, et al.
Published: (2022)

Function Based Isolation Forest (FuBIF): A Unifying Framework for Interpretable Isolation-Based Anomaly Detection
by: Arcudi, Alessio, et al.
Published: (2025)

Forest-ORE: Mining Optimal Rule Ensemble to interpret Random Forest models
by: Maissae, Haddouchi, et al.
Published: (2024)

Properties of fairness measures in the context of varying class imbalance and protected group ratios
by: Brzezinski, Dariusz, et al.
Published: (2024)

Jump Like A Squirrel: Optimized Execution Step Order for Anytime Random Forest Inference
by: Biebert, Daniel, et al.
Published: (2026)

Nearest-Neighbour-Induced Isolation Similarity and its Impact on Density-Based Clustering
by: Qin, Xiaoyu, et al.
Published: (2019)

Interpretable Network-assisted Random Forest+
by: Tang, Tiffany M., et al.
Published: (2025)

Simplifying Random Forests' Probabilistic Forecasts
by: Koster, Nils, et al.
Published: (2024)

Ordinal Mixed-Effects Random Forest
by: Bergonzoli, Giulia, et al.
Published: (2024)

Global Censored Quantile Random Forest
by: Zhou, Siyu, et al.
Published: (2024)

Random Forest Autoencoders for Guided Representation Learning
by: Aumon, Adrien, et al.
Published: (2025)

Explainable Unsupervised Anomaly Detection with Random Forest
by: Harvey, Joshua S., et al.
Published: (2025)

Pure interaction effects unseen by Random Forests
by: Blum, Ricardo, et al.
Published: (2024)