
What's a good imputation to predict with missing values?
How to learn a good predictor on data with missing values? Most efforts ...
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SHAFF: Fast and consistent SHApley eFfect estimates via random Forests
Interpretability of learning algorithms is crucial for applications invo...
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Generalizing a causal effect: sensitivity analysis and missing covariates
While a randomized controlled trial (RCT) readily measures the average t...
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MDA for random forests: inconsistency, and a practical solution via the SobolMDA
Variable importance measures are the main tools to analyze the blackbox...
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Analyzing the treelayer structure of Deep Forests
Random forests on the one hand, and neural networks on the other hand, h...
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Neumann networks: differential programming for supervised learning with missing values
The presence of missing values makes supervised learning much more chall...
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Interpretable Random Forests via Rule Extraction
We introduce SIRUS (Stable and Interpretable RUle Set) for regression, a...
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Linear predictor on linearlygenerated data with missing values: non consistency and solutions
We consider building predictors when the data have missing values. We st...
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Trees, forests, and impuritybased variable importance
Tree ensemble methods such as random forests [Breiman, 2001] are very po...
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SIRUS: making random forests interpretable
Stateoftheart learning algorithms, such as random forests or neural n...
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AMF: Aggregated Mondrian Forests for Online Learning
Random Forests (RF) is one of the algorithms of choice in many supervise...
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On the consistency of supervised learning with missing values
In many application settings, the data are plagued with missing features...
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Minimax optimal rates for Mondrian trees and forests
Introduced by Breiman (2001), Random Forests are widely used as classifi...
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Universal consistency and minimax rates for online Mondrian Forests
We establish the consistency of an algorithm of Mondrian Forests, a rand...
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Neural Random Forests
Given an ensemble of randomized regression trees, it is possible to rest...
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A Random Forest Guided Tour
The random forest algorithm, proposed by L. Breiman in 2001, has been ex...
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Consistency of random forests
Random forests are a learning algorithm proposed by Breiman [Mach. Learn...
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Erwan Scornet
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