Regression Conformal Prediction with Nearest Neighbours

Regression Conformal Prediction with Nearest Neighbours

In this paper we apply Conformal Prediction (CP) to the k -Nearest Neighbours Regression (k -NNR) algorithm and propose ways of extending the typical nonconformity measure used for regression so far. Unlike traditional regression methods which produce point predictions, Conformal Predictors output predictive regions that satisfy a given confidence level. The regions produced by any Conformal Pr...

Smoothing Using Nearest Neighbours

Feature Reduction and Nearest Neighbours

Feature reduction is a major preprocessing step in the analysis of highdimensional data, particularly from biomolecular high-throughput technologies. Reduction techniques are expected to preserve the relevant characteristics of the data, such as neighbourhood relations. We investigate the neighbourhood preservation properties of feature reduction empirically and theoretically. Our results indic...

Applications of Nearest Neighbours Statistics

Jorg D. Wichard, Ulrich Parlitz and Werner Lauterborn Drittes Physikalisches Institut, Georg-August-Universitat Gottingen, D-37073 Gottingen, Germany [email protected] Abstract| Based on an e cient method for nding nearest neighbours in the phase space of a dynamical system, several applications of nearest neighbour statistics are presented, including methods to detect nonstationarity...

Finding and evaluating sets of nearest neighbours

In this paper, we consider two applications of distributional similarity measures, probability estimation and prediction of semantic similarity. We investigate whether high performance in one application area is correlated with high performance in the other. This work also provides an evaluation of two state-of-the-art distributional similarity measures and introduces a variant of one. Further,...