Predictions and forecasts of machine learning models should take the form of probability
distributions, aiming to increase the quantity of information communicated to end users …

Predictions and forecasts of machine learning models should take the form of probability
distributions, aiming to increase the quantity of information communicated to end users …

Ensemble learning is widely used in applications to make predictions in complex decision
problems---for example, averaging models fitted to a sequence of samples bootstrapped …

Kernel survival analysis methods predict subject-specific survival curves and times using
information about which training subjects are most similar to a test subject. These most …

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 …

The current work addresses an industrial problem related to injection moulding
manufacturing with focus on mould wear-out prediction. Real data sets are provided by an …

Few systematic comparisons of methods for constructing survival trees and forests exist in
the literature. Importantly, when the goal is to predict a survival time or estimate a survival …

Survival modeling concerns predicting whether or not an event will occur before or on a
given point in time. In a recent study, the conformal prediction framework was applied to this …

In this paper, we introduce a prediction algorithm founded on conformal prediction, tailored
for constructing prediction intervals in the context of censored survival data. Conformal …

In the current state of AI development, it is reasonable to think that AI will continue to expand
and be increasingly utilized across different fields, highly impacting every aspect of …