Survival regression with proper scoring rules and monotonic neural networks

Survival regression with proper scoring rules and monotonic neural networks

We consider frequently used scoring rules for right-censored survival regression models such as time-dependent concordance, survival-CRPS, integrated Brier score and integrated binomial log-likelihood, and prove that neither of them is a proper scoring rule. This means that the true survival distrib...

Bibliografiset tiedot
Päätekijät:	Rindt, D, Hu, R, Steinsaltz, D, Sejdinovic, D
Aineistotyyppi:	Conference item
Kieli:	English
Julkaistu:	Journal of Machine Learning Research 2022

Samankaltaisia teoksia

A kernel- and optimal transport- based test of independence between covariates and right-censored lifetimes
Tekijä: Rindt, D, et al.
Julkaistu: (2020)

Consistency of permutation test s of independence usingdistance covariance, HSIC and dHSIC
Tekijä: Rindt, D, et al.
Julkaistu: (2021)

Proper local scoring rules
Tekijä: Parry, M, et al.
Julkaistu: (2011)

Proper local scoring rules on discrete sample spaces
Tekijä: Dawid, A, et al.
Julkaistu: (2011)

Tailored proper scoring rules elicit decision weights
Tekijä: Arthur Carvalho
Julkaistu: (2015-01-01)

Proper scoring rules for multivariate probabilistic forecasts based on aggregation and transformation
Tekijä: R. Pic, et al.
Julkaistu: (2025-03-01)

Nonparametric independence testing and regression for time-to-event data
Tekijä: Rindt, D
Julkaistu: (2021)

Proper scoring rules, gradients, divergences, and entropies for paths and time series
Tekijä: Bonnier, P, et al.
Julkaistu: (2021)

A kernel log-rank test of independence for right-censored data
Tekijä: Fernández, T, et al.
Julkaistu: (2021)

An IRT forecasting model: linking proper scoring rules to item response theory
Tekijä: Yuanchao Emily Bo, et al.
Julkaistu: (2017-03-01)

An IRT forecasting model: linking proper scoring rules to item response theory
Tekijä: Yuanchao Emily Bo, et al.
Julkaistu: (2017-03-01)

Multi-quantile systemic financial risk based on a monotone composite quantile regression neural network
Tekijä: Chao Ren, et al.
Julkaistu: (2024-11-01)

Filtration of Non-Monotonic Rules for Fuzzy Rule Base Compression
Tekijä: Alexander Gegov, et al.
Julkaistu: (2014-04-01)

REGRESI SPLINES BENTUK-TERBATAS MONOTON (MONOTONE SHAPE-RESTRICTED REGRESSION SPLINES)
Tekijä: , ESTRI PURWANI, et al.
Julkaistu: (2013)

Large scale tensor regression using kernels and variational inference
Tekijä: Hu, R, et al.
Julkaistu: (2021)

Monotone rewritability and the analysis of queries, views, and rules
Tekijä: Benedikt, M, et al.
Julkaistu: (2024)

Rethinking the rules of financial accounting : examining the rules for proper reporting /
Tekijä: 181365 Anthony, Robert N. (Robert Newton), 1916-2006
Julkaistu: (2004)

Nonlinear Survival Regression Using Artificial Neural Network
Tekijä: Akbar Biglarian, et al.
Julkaistu: (2013-01-01)

A simple method for pairwise monotone regression /
Tekijä: 452000 Johnson, Richard M.

Bayesian approaches to distribution regression
Tekijä: Law, H, et al.
Julkaistu: (2018)

Morphological inflectional rules for Karelian Proper verbs
Tekijä: Natalia Krizhanovskaya, et al.
Julkaistu: (2022-07-01)

The Ruling Discourse on Proper Womanhood in the Hungarian Parliament
Tekijä: Irén Annus
Julkaistu: (2014-09-01)

Generalized monotonic regression using random change points.
Tekijä: Holmes, C, et al.
Julkaistu: (2003)

Statistical methods for paleodemography on fossil assemblages having small numbers of specimens: an investigation of dinosaur survival rates
Tekijä: Steinsaltz, D, et al.
Julkaistu: (2011)

Interpretation of trained neural networks by rule extraction
Tekijä: Palade, V, et al.
Julkaistu: (2001)

Dual active-set algorithm for optimal 3-monotone regression
Tekijä: Gudkov, Alexandr A., et al.
Julkaistu: (2022-05-01)

Modelling the monotonic and cyclic behaviour of sands using Artificial Neural Networks
Tekijä: Chen Weixian, et al.
Julkaistu: (2021-01-01)

Complete regression of melanocytic nevi: clues for proper diagnosis
Tekijä: Maria Leticia Cintra, et al.

EVALUATION OF MODERN HERITAGE ASSETS IN POZNAN USING MONOTONIC DECISION RULES
Tekijä: A. Rumież, et al.
Julkaistu: (2023-06-01)

Novel Art-Based Neural Network Models For Pattern Classification, Rule Extraction And Data Regression
Tekijä: Yap , Keem Siah
Julkaistu: (2010)

Feature-to-feature regression for a two-step conditional independence test
Tekijä: Zhang, Q, et al.
Julkaistu: (2017)

DR-ABC: Approximate Bayesian computation with kernel-based distribution regression
Tekijä: Mitrovic, J, et al.
Julkaistu: (2016)

"Proper" Shift Rules for Derivatives of Perturbed-Parametric Quantum Evolutions
Tekijä: Dirk Oliver Theis
Julkaistu: (2023-07-01)

Rule Talk: Instructing Proper Play With Impersonal Deontic Statements
Tekijä: Jörg Zinken, et al.
Julkaistu: (2021-07-01)

Classification, Regression, and Survival Rule Induction with Complex and M-of-N Elementary Conditions
Tekijä: Cezary Maszczyk, et al.
Julkaistu: (2024-03-01)

Unbiased Isotonic Regression Tree for Discovering Hidden Heterogeneity in Monotonicity Constraints
Tekijä: Doowon Choi
Julkaistu: (2025-01-01)

Monotone Regression: A Simple and Fast O(n) PAVA Implementation
Tekijä: Frank M. T. A. Busing
Julkaistu: (2022-05-01)

On the Monotonicity and Positivity of Physics-Informed Neural Networks for Highly Anisotropic Diffusion Equations
Tekijä: Wenjuan Zhang, et al.
Julkaistu: (2022-09-01)

Robust and provably monotonic networks
Tekijä: Ouail Kitouni, et al.
Julkaistu: (2023-01-01)

Predicting successful draft outcome in Australian Rules football: Model sensitivity is superior in neural networks when compared to logistic regression.
Tekijä: Jacob Jennings, et al.
Julkaistu: (2024-01-01)