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Inherently Interpretable Tree Ensemble Learning

Inherently Interpretable Tree Ensemble Learning

Zebin Yang
Agus Sudjianto
Xiaoming Li
Aijun Zhang
ArXiv (abs)PDFHTML

Papers citing "Inherently Interpretable Tree Ensemble Learning"

6 / 6 papers shown
Title
Designing Inherently Interpretable Machine Learning Models
Designing Inherently Interpretable Machine Learning Models
Agus Sudjianto
Aijun Zhang
FaML
41
31
0
02 Nov 2021
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions
Zebin Yang
Aijun Zhang
Agus Sudjianto
FAtt
150
128
0
16 Mar 2020
CatBoost: gradient boosting with categorical features support
CatBoost: gradient boosting with categorical features support
Anna Veronika Dorogush
Vasily Ershov
Andrey Gulin
140
1,337
0
24 Oct 2018
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.1K
21,939
0
22 May 2017
XGBoost: A Scalable Tree Boosting System
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
809
38,961
0
09 Mar 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.2K
16,990
0
16 Feb 2016

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