Signed-Error Conformal Regression
نویسندگان
چکیده
This paper suggests a modification of the Conformal Prediction framework for regression that will strengthen the associated guarantee of validity. We motivate the need for this modification and argue that our conformal regressors are more closely tied to the actual error distribution of the underlying model, thus allowing for more natural interpretations of the prediction intervals. In the experimentation, we provide an empirical comparison of our conformal regressors to traditional conformal regressors and show that the proposed modification results in more robust two-tailed predictions, and more efficient one-tailed predictions.
منابع مشابه
Does intensity modulation increase target dose calculation errors of conventional algorithms for lung SBRT?
PURPOSE Conventional dose algorithms (Type A and Type B) for lung SBRT can display considerable target dose errors compared to Type-C algorithms. Intensity-modulated techniques (IMRT/VMAT) are increasingly being utilized for lung SBRT. Therefore, our study aimed to assess whether intensity modulation increased target dose calculation errors by conventional algorithms over conformal techniques. ...
متن کاملConformal Predictions for Information Fusion A Comparative Study of P-Value Combination Methods
The increased availability of a wide range of sensing technologies over the last few decades has resulted in an equivalent increased need for reliable information fusion methods in machine learning applications. While existing theories such as the Dempster-Shafer theory and the possibility theory have been used for several years now, they do not provide guarantees of error calibration in inform...
متن کاملModified signed log-likelihood test for the coefficient of variation of an inverse Gaussian population
In this paper, we consider the problem of two sided hypothesis testing for the parameter of coefficient of variation of an inverse Gaussian population. An approach used here is the modified signed log-likelihood ratio (MSLR) method which is the modification of traditional signed log-likelihood ratio test. Previous works show that this proposed method has third-order accuracy whereas the traditi...
متن کاملConformal sets in neural network regression
This paper is concerned with predictive regions in regression models, especially neural networks. We use the concept of conformal prediction (CP) to construct regions which satisfy given confidence level. Conformal prediction outputs regions, which are automatically valid, but their width and therefore usefulness depends on the used nonconformity measure. A nonconformity measure should tell us ...
متن کاملCorrection of Regression Predictions Using the Secondary Learner on the Sensitivity Analysis Outputs
For a given regression model, each individual prediction may be more or less accurate. The average accuracy of the system cannot provide the error estimate for a single particular prediction, which could be used to correct the prediction to a more accurate value. We propose a method for correction of the regression predictions that is based on the sensitivity analysis approach. Using prediction...
متن کامل