cumulative_hazard_to_survival

Helper function to transform between CHF and survival function

Survival analysis models are commonly used in medicine and other areas. Many of them
are too complex to be interpreted by human. Exploration and explanation is needed, but
standard methods do not give a broad enough picture. 'survex' provides easy-to-apply
methods for explaining survival models, both complex black-boxes and simpler statistical models.
They include methods specific to survival analysis such as SurvSHAP(t) introduced in Krzyzinski et al., (2023)
<doi:10.1016/j.knosys.2022.110234>, SurvLIME described in Kovalev et al., (2020) <doi:10.1016/j.knosys.2020.106164> as well as
extensions of existing ones described in Biecek et al., (2021) <doi:10.1201/9780429027192>.

Mikołaj Spytek

survex

Explainable Machine Learning in Survival Analysis

Mateusz Krzyziński

Sophie Langbein

Hubert Baniecki

Lorenz A. Kapsner

Przemyslaw Biecek

cumulative_hazard_to_survival function

<dl><dt>hazard_functions</dt>
<dd>matrix or vector, with each row representing a cumulative hazard function</dd></dl>

Arguments

Transform Cumulative Hazard to Survival — cumulative_hazard_to_survival

<dl>

<dt>hazard_functions</dt>
<dd>matrix or vector, with each row representing a cumulative hazard function</dd>

</dl>

cumulative_hazard_to_survival: Transform Cumulative Hazard to Survival

Description

Usage

Value

Arguments

Examples