T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP

by   Jiaye Teng, et al.

It is challenging to deal with censored data, where we only have access to the incomplete information of survival time instead of its exact value. Fortunately, under linear predictor assumption, people can obtain guaranteed coverage for the confidence band of survival time using methods like Cox Regression. However, when relaxing the linear assumption with neural networks (e.g., Cox-MLP (Katzman et al., 2018; Kvamme et al., 2019)), we lose the guaranteed coverage. To recover the guaranteed coverage without linear assumption, we propose two algorithms based on conformal inference. In the first algorithm WCCI, we revisit weighted conformal inference and introduce a new non-conformity score based on partial likelihood. We then propose a two-stage algorithm T-SCI, where we run WCCI in the first stage and apply quantile conformal inference to calibrate the results in the second stage. Theoretical analysis shows that T-SCI returns guaranteed coverage under milder assumptions than WCCI. We conduct extensive experiments on synthetic data and real data using different methods, which validate our analysis.



There are no comments yet.


page 5

page 6

page 8

page 9

page 18

page 19

page 20

page 21


Conformalized Survival Analysis

Existing survival analysis techniques heavily rely on strong modelling a...

Optimization from Structured Samples for Coverage Functions

We revisit the optimization from samples (OPS) model, which studies the ...

A comparison of some conformal quantile regression methods

We compare two recently proposed methods that combine ideas from conform...

Improving Coverage and Runtime Complexity for Exact Inference in Non-Projective Transition-Based Dependency Parsers

We generalize Cohen, Gómez-Rodríguez, and Satta's (2011) parser to a fam...

Classification with Valid and Adaptive Coverage

Conformal inference, cross-validation+, and the jackknife+ are hold-out ...

On Some Problems of Confidence Region Construction

The general problem of constructing confidence regions is unsolved in th...

Carving model-free inference

Many scientific studies are modeled as hierarchical procedures where the...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.