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- Corpus ID: 3730942

@inproceedings{Hothorn2015ctreeC, title={ctree : Conditional Inference Trees}, author={Torsten Hothorn and Kurt Hornik and Wirtschaftsuniversit{\"a}t Wien and Achim Zeileis}, year={2015}, url={https://api.semanticscholar.org/CorpusID:3730942}}

- T. Hothorn, K. Hornik, A. Zeileis
- Published 2015
- Computer Science, Mathematics

This vignette describes the new reimplementation of conditional inference trees (CTree) in the R package partykit . CTree is a non-parametric class of regression trees embedding tree-structured…

81 Citations

5

14

34

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## Topics

Conditional Inference Tree (opens in a new tab)Partykit (opens in a new tab)Inference Procedure (opens in a new tab)Censored (opens in a new tab)Regression Trees (opens in a new tab)Tree-structured Regression Models (opens in a new tab)Covariates (opens in a new tab)R Package (opens in a new tab)Measurement Scales (opens in a new tab)

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MCCE is introduced, a novel counterfactual explanation method that generates on-manifold, actionable and valid counterfactuals by modeling the joint distribution of the mutable features given the immutable features and the decision by modeling the joint distribution of the mutable features given the immutable features and the decision.

- T. EmuraWei-Chern HsuW. Chou
- 2023

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This work proposes a novel matrix-based algorithm in order to tests a number of nodes simultaneously via stabilized score tests and proposes a recursive partitioning algorithm to construct a survival tree and develops the original R package uni.survival.tree (https://cran.r-project.org/package=uni. survival.tree) for implementation.

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- 2017

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This paper introduces an unsupervised and generic technique to detect significant variants in event logs by applying existing, well-proven data mining techniques for recursive partitioning driven by conditional inference over event attributes.

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- 2021

Mathematics, Medicine

Stat. Anal. Data Min.

The proposed SurvCART algorithm utilizes the “conditional inference” framework that selects splitting variable via parameter instability test and subsequently finds the optimal split based on some maximally chosen statistic.

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- 2020

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The field is urged to recall its roots of interpretable, data-driven modeling in statistics and (rule-based) ML, but also to consider other areas such as sensitivity analysis, causal inference, and the social sciences.

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This paper reviews extensively many popularly used state-of-the-art decision tree-based techniques for classification and regression and presents a survey of morethan forty years of research that has been emphasized on the application of decision trees in bothclassification and regression.

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## 25 References

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Mathematics, Computer Science

A unified framework for recursive partitioning is proposed which embeds tree-structured regression models into a well defined theory of conditional inference procedures and it is shown that the predicted accuracy of trees with early stopping is equivalent to the prediction accuracy of pruned trees with unbiased variable selection.

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The regression-tree methodology is extended to right-censored response variables by replacing the conventional splitting rules with rules based on the Tarone-Ware or Harrington-Fleming classes of…

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Mathematics, Computer Science

This workshop introduces students to current methods for analyzing categorical data, with its principal focus being regression models for categorical outcomes. We will consider models for binary,…

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Mathematics

Biometrics

A method is developed for obtaining tree-structured relative risk estimates for censored survival data using a recursive partitioning algorithm that adopts most aspects of the widely used Classification and Regression Tree (CART) algorithm.

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- 2004

Mathematics

- 89
- PDF

- Joseph D. Conklin
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Mathematics

Technometrics

As a consultant, I am always on the lookout for new books that help me do my job better. Iwould recommend practitioners of regression, that is, probably most of us, to read and use this book. Anthony…

- 2,473

- A. WhiteWei Zhong Liu
- 2004

Computer Science, Mathematics

Machine Learning

A fresh look is taken at the problem of bias in information-based attribute selection measures, used in the induction of decision trees and it is concluded that approaches which utilise the chi-square distribution are preferable because they compensate automatically for differences between attributes in the number of levels they take.

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- PDF

- N. Speybroeck
- 2011

Medicine, Computer Science

International Journal of Public Health

As with stepwise linear regression procedures, adding variables will continuously increase the fit of the model to the data, but at the cost of increasing the true fit to an independent data set.

- 12,942
- Highly Influential

- Hyun Gon NohM. SongSung Hyun Park
- 2004

Computer Science, Mathematics

Comput. Stat. Data Anal.

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- H. StrasserChristian H. Weber
- 1999

Mathematics

In this paper limit theorems for the conditional distributions of linear test statistics are proved. The assertions are conditioned by the sigma-field of permutation symmetric sets. Limit theorems…

- 295
- Highly Influential
- PDF

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