Generalized Prediction Intervals for Arbitrary Distributed High-Dimensional Data

Details Generalized Prediction Intervals for Arbitrary Distributed High-Dimensional Data Generalized Prediction Intervals for Arbitrary Distributed High-Dimensional Data

2008-09-19

arxiv.org/abs/0809.3352v1

Computer Science

Computer Vision and Pattern Recognition

13 pages, 3 figures

Scientific paper

This paper generalizes the traditional statistical concept of prediction intervals for arbitrary probability density functions in high-dimensional feature spaces by introducing significance level distributions, which provides interval-independent probabilities for continuous random variables. The advantage of the transformation of a probability density function into a significance level distribution is that it enables one-class classification or outlier detection in a direct manner.

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