In this study, we describe changes in the nature of Crew Resource Management (CRM) training in commercial aviation, including its shift from cockpit to crew resource management. Validation of the impact of CRM is discussed. Limitations of CRM, including lack of cross-cultural generality are considered. An overarching framework that stresses error management to increase acceptance of CRM concept...

In the context of binary classification, we define disagreement as a measure of how often two independently-trained models differ in their classification of unlabeled data. We explore the use of disagreement for error estimation and model selection. We call the procedure co-validation, since the two models effectively (in)validate one another by comparing results on unlabeled data, which we ass...

Generalizability in a multi-subject fMRI study is investigated. The analysis is based on principal and independent component representations. Subsequent supervised learning and classification is carried out by canonical variates analysis and clustering methods. The generalization error is estimated by cross-validation, forming the so-called learning curves. The fMRI case story is a motor-contro...

A statistical theory for overtraining is proposed. The analysis treats realizable stochastic neural networks, trained with KullbackLeibler loss in the asymptotic case. It is shown that the asymptotic gain in the generalization error is small if we perform early stopping, even if we have access to the optimal stopping time. Considering cross-validation stopping we answer the question: In what ra...

Clinical trials increasingly employ medical imaging data in conjunction with supervised classifiers, where the latter require large amounts of training data to accurately model the system. Yet, a classifier selected at the start of the trial based on smaller and more accessible datasets may yield inaccurate and unstable classification performance. In this paper, we aim to address two common con...

The identification of chair rise phases is a prerequisite for quantifying sit-to-stand movements. The aim of this study is to validate seat-off and seat-on detection using a single-body-fixed sensor against detection based on chair switches. A single sensor system with three accelerometers and three gyroscopes was fixed around the waist. Synchronized on-off switches were placed under the chair....

This work is concerned with the estimation of a classifier’s accuracy. We first review some existing methods for error estimation, focusing on cross-validation and bootstrap, and motivate the use of kernel-based smoothing for small sample size. We use the term data cloning to refer to the process of (re)sampling the data via kernel-based smoothed bootstrap. A number of novel estimators based on...

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