In this work, we proposed to use the Zoomed Ranking approach to rank and select time series models. Zoomed Ranking, originally proposed to generate a ranking of candidate algorith...
The integration of multiple predictors promises higher prediction accuracy than the accuracy that can be obtained with a single predictor. The challenge is how to select the best ...
We study the domain of dominant competence of six popular classifiers in a space of data complexity measurements. We observe that the simplest classifiers, nearest neighbor and li...
While learning ensembles have been widely used for various pattern recognition tasks, surprisingly, they have found limited application in problems related to medical image analysi...
Anant Madabhushi, Jianbo Shi, Michael D. Feldman, ...
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...